tag:blogger.com,1999:blog-61463764833745897792024-03-02T17:46:51.912-08:00Wiring the Brainhow the brain wires itself up during development, how the end result can vary in different people and what happens when it goes wrongKevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.comBlogger140125tag:blogger.com,1999:blog-6146376483374589779.post-79088005896819111942024-01-22T11:25:00.000-08:002024-01-22T11:25:56.911-08:00Undetermined - a response to Robert Sapolsky. Part 4 - Loosening the treaties of fate<span lang="EN-GB">In <a href="http://www.wiringthebrain.com/2024/01/undetermined-response-to-robert.html" target="_blank">Part 3</a> of this series, I argued that
organisms really do think about what to do, really do come to their reasons by
reasoning, and really do make decisions, in ways that cannot be pre-determined.
</span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span class="css-1qaijid"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">If the neural computations are causally sensitive to
semantic content, rather than detailed syntax, and those semantics relate to
organism-level concepts, and all that information is integrated in a hugely
contextually interdependent way, and is used to direct behavior over nested
timescales, in ways that cannot be either algorithmically or physically
pre-specified, based on criteria configured into the circuits derived from
learning, which embody reasons of the organism and not any of its parts, then I
would say that <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">just is</i></b> the organism – as an integrated self with continuity
through time – deciding what to do.</span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">I also argued that more fundamental principles of </span><span lang="EN-GB">indeterminacy and
emergence and organisation are the things that enable organisms themselves to come to be in
charge of what happens</span><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB"> </span></b></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">But
what if the universe as a whole is deterministic? </span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">How could mental states – or any states of
the whole organism – have causal power over how the system evolves, when all
the causes are supposedly located at the lowest levels? How can we escape from
the confines of reductionism? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky considers the question of physical
pre-determinism at the lowest levels of reality and comes to a similar initial
conclusion as I do, which is that the general consensus from physics is that the
low-level laws of quantum mechanics are not deterministic: </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB" style="font-size: 10.5pt;">For our purposes,
the main points are that in the view of most of the savants, the subatomic
universe works on a level that is fundamentally indeterministic on both an
ontic and epistemic level. (page 213)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, he argues that the law of large
numbers means that any such random events at the level of individual molecules
will be averaged out across the system and will thus not manifest at levels we
care about. Oddly, one of his arguments for this is that the system in question
is <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">not
deterministic at those higher levels</i></b>:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">People in this
business view the brain not only as “noisy” in this sense but also as “warm” and
“wet,” the messy sort of living environment that biases against quantum effects
persisting. (page 221)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The argument thus seems to be that
individual random events at low levels get washed out <span style="mso-bidi-font-style: normal;">by higher-level randomness</span>: </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal" style="line-height: 10.7pt; mso-layout-grid-align: none; mso-pagination: none; text-align: justify; text-autospace: none; text-justify: inter-ideograph;"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">…quantum effects
are washed away amid the decohering warm, wet noise of the brain as one scales
up. (page 238)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It’s not clear where, in this picture, <i style="mso-bidi-font-style: normal;">the higher-level randomness</i> is supposed
to come from, but actually, for the purposes of the discussion of free will,
it’s sufficient that it exists. The important point is that physical
pre-determinism does not hold, <i style="mso-bidi-font-style: normal;">at any
level</i>. This means the evolution of the system through time should not be completely pre-determined, but open. <br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky still maintains a hard <i style="mso-bidi-font-style: normal;">reductionist</i> stance, however, and while
he engages with the concepts of non-linearity in complex systems, he fails to
make a crucial connection. He writes that the reductionist tradition of only
studying linear relationships in isolation: </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="Default"><span style="font-size: 10.5pt; mso-bidi-font-family: "Times New Roman";">…guaranteed
the incorrect conclusion that the world is mostly about linear, additive
predictability and nonlinear chaoticism was a weird anomaly that could mostly
be ignored. Until it couldn’t be anymore, as it became clear that chaoticism
lurked behind the most interesting complicated things. A cell, a brain, a
person, a society, was more like the chaoticism of a cloud than the
reductionism of a watch. (page 145)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, based on the literature on chaotic
systems, he concludes:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">Even if
chaoticism is unpredictable, </span><i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">it is still deterministic</span></i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">. (page 148)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Now, it is true that many of the classic
examples of chaotic systems – or, more precisely, computer simulations of such
systems – are deterministic. The evolution of such simulations can be extremely
sensitive to slight changes in the values of different parameters at far
decimal points, which can have unexpected, <i style="mso-bidi-font-style: normal;">but
consistent</i>, influences over future states. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, that does not mean that chaotic
systems in the real world – outside of computer simulations – must also be<i style="mso-bidi-font-style: normal;"> </i>deterministic. If there is some real
indeterminacy in the physical parameters of a system (which we’ve established
there must be), <i style="mso-bidi-font-style: normal;">and</i> it has the kind
of complex, non-linear dynamics that make it chaotic, well then it will be
genuinely unpredictable, not just in practice, but in principle. The parameters
describing its future states just <a href="https://arxiv.org/abs/1909.04514" target="_blank">won’t have truth values</a> in the present,
beyond some decimal point. I argue in <a href="https://press.princeton.edu/books/hardcover/9780691226231/free-agents" target="_blank"><i style="mso-bidi-font-style: normal;">Free
Agents</i></a> that the universe as a whole is like that. It operates a kind of
just-in-time reality, where the future is radically open. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">How
could indeterminacy help?</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A common argument goes like this: if my
behavior is caused by deterministic physical events, then I don’t have free
will. But if it’s caused by random physical events, then I also don’t have free
will. Sapolsky rightly raises this challenge:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">Even if quantum
effects bubbled up enough to make our macro world as indeterministic as our
micro one is, this would not be a mechanism for free will worth wanting. That
is, unless you figure out a way where we can supposedly harness the randomness
of quantum indeterminacy to direct the consistencies of who we are. (page 230)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This almost gets us where we need to go,
but misses what for me is possibly the most crucial point in this whole debate.
For agency to emerge and be exercised, living organisms don’t have to <i style="mso-bidi-font-style: normal;">harness </i>the indeterminacy – they just
have to take advantage of the causal opportunities it presents. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As my student, Henry Potter, puts it:
“Indeterminacy is little more than a pre-condition for agency. It is the
background on which a story of agency can be built, not a leading character in
that story itself.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, Sapolsky continues:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">I see two broad
ways of thinking about how we might harness, co‑opt, and join forces with
randomness for moral consistency. In a “filtering” model, randomness is
generated indeterministically, the usual, but the agentic “you” installs a
filter up top that allows only some of the randomness that has bubbled up to
pass through and drive behavior. In contrast, in a “messing with” model, your
agentic self reaches all the way down and messes with the quantum indeterminacy
itself in a way that produces the behavior supposedly chosen. (page 231)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is a nice distinction, but I don’t
think either of these models is apt, and a third possibility is not considered.
We do indeed use “filtering” mechanisms all the time – that’s how we evaluate
possible actions and select one, for example. But this is not, except under
certain circumstances <a href="https://time.com/6549514/brain-randomness-creativity-essay/" target="_blank">where it’s useful</a>, allowing some of the randomness “to
drive behavior”. And I agree with Sapolsky that the “messing with” model makes
no sense. We don’t need top-down causation to reach a ghostly tendril down and
control what would otherwise be a random quantum event.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The important point is much more
fundamental. I’m going to take the odd step of quoting him quoting me:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">In the words of
Irish neuroscientist Kevin Mitchell, “indeterminacy creates some elbow room. .
. . What randomness does, it is posited, is to introduce some room, <a href="https://pubmed.ncbi.nlm.nih.gov/29961596/" target="_blank">some causal slack in the system</a>, for higher-order factors to exert a </span><i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">causal </span></i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">influence” (my emphasis). (page
235).</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">He seems to take me to be arguing here for
a “messing with” sort of mechanism, but I’m doing quite the opposite. The
causal influence that is exerted is on <i style="mso-bidi-font-style: normal;">how
the whole system evolves at macro levels</i>. The
organism doesn’t care how the system evolves on the micro level. Those details
are not relevant. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">As physicist and philosopher George Ellis <a href="https://pubmed.ncbi.nlm.nih.gov/30740063/" target="_blank">puts it</a>: "Much randomness occurs at the molecular level, which enables higher functions to select lower level outcomes according to higher level needs."</span><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">We don’t need (and generally don’t want) specific random
events to determine the outcome. We just need some pervasive indeterminacy to
exist such that the low-level forces <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">under-determine</i></b> the outcome, leaving
some room for higher-order organisation to emerge, with causal efficacy over
how the system evolves (because the system has been configured in functional
ways by natural selection). This is not “messing with”, this is <i style="mso-bidi-font-style: normal;">taking advantage of.</i></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky disagrees with philosophers Robert
Kane and Christian List:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="Pa31" style="text-align: justify; text-justify: inter-ideograph;"><span style="font-size: 10.5pt;">Robert Kane states the same: “We think we have to
become originators at the micro- level [to explain free will] . . . and we
realize, of course, that we cannot do that. But we do not have to. It is the
wrong place to look. We do not have to micro-manage our individual neurons one
by one.” </span><span class="A16"><span style="font-size: 6.0pt;"></span></span></p>
<p class="Default"> </p>
<p class="MsoNormal"><span lang="EN-GB" style="font-size: 10.5pt;">So these free-
will believers accept that a neuron cannot defy the physical universe and have
free will. But a bunch of them can; to quote List, “free will and its
prerequisites are emergent, higher-level phenomena.” (page 192) </span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">While I also disagree with the <i style="mso-bidi-font-style: normal;">compatibilist version</i> of these arguments
(where fundamental indeterminacy is deemed to be unnecessary for high-level
freedom), the general point is sound (especially if we can just help ourselves
to fundamental indeterminacy, because that’s our best understanding of the
relevant physics).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We really don’t have to micro-manage our
individual neurons – that’s the whole point. We don’t have to care what every
neuron is doing because the system is configured to be <i style="mso-bidi-font-style: normal;"><a href="https://osf.io/preprints/psyarxiv/dfkrv" target="_blank">sensitive to the meaning</a> of high-level patterns</i>, not the precise
details of every action potential or every synaptic vesicle fusing or ion
channel opening. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Emergence
and downward causation</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The idea that an organism can have causal
power, as a whole entity, as a <i style="mso-bidi-font-style: normal;">self</i>,
depends on concepts of emergence and downward causality. It’s just not possible
to grasp the main argument without engaging with these concepts. It is thus
disappointing that Sapolsky mostly simply chooses not to: </span></p>
<p class="Default"> </p>
<p class="Default"><i style="mso-bidi-font-style: normal;"><span style="font-size: 11.0pt;">Thus, a lot of people have linked emergence and free will; I will not
consider most of them because, to be frank, I can’t understand what they’re
suggesting, and to be franker, I don’t think the lack of comprehension is
entirely my fault. </span></i><span style="font-size: 11.0pt;">(Pages 192-3)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Instead, he argues that:</span></p>
<p class="Default"> </p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt; mso-bidi-font-family: "Times New Roman";">Emergent systems
can’t make the bricks that built them stop being brick-ish (page 202).</span></i><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;"></span></i></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That latter point is true, but misses the larger
idea, which is simply that the way a system is organised can (non-magically) constrain
the behavior of its components, <i style="mso-bidi-font-style: normal;">without changing
their individual nature</i>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">He states:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;">…the core belief among this style of emergent
free-willers is that emergent states can in fact change how neurons work, and
that free will depends on it. It is the assumption that emergent systems “have
base elements that behave in novel ways when they operate as part of the
higher-order system.” (Page 201).</span></i></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But if “emergent states” means, for
example, what you’re thinking about, then <i style="mso-bidi-font-style: normal;">of
course</i> that alters how neurons work. That is precisely how nervous systems as
a whole work – by one neuron altering how another one is working. And by
population dynamics affecting how each individual neuron is working. And by
patterns at one level – patterns <i style="mso-bidi-font-style: normal;">that
mean something</i> – setting the context and criteria for how neurons at
another level work. This isn’t magic. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In the same way, the electrons in your
computer are constrained by the particular software that’s running. This doesn’t
change the <i style="mso-bidi-font-style: normal;">properties</i> of the
individual electrons, but <b>it absolutely does mean</b> that electrons are <i style="mso-bidi-font-style: normal;">behaving</i> differently when they’re in a
microprocessor than when they’re not.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It’s thus a shame that Sapolsky does not
engage with the kind of literature – by people like <a href="https://www.youtube.com/watch?v=kjroe38FATE" target="_blank">Alicia Juarrero</a> and <a href="https://en.wikipedia.org/wiki/George_F._R._Ellis" target="_blank">George Ellis</a>, for example – that provides exactly the resources we need to understand
how complex systems can be organised in functional ways, where constraints and
history are just as crucial to understanding causation as local, instantaneous
physical forces. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB"> </span></b></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Mental
causation</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Perhaps the key stumbling block in
understanding how things can be up to us, in a meaningful sense, is the idea of
mental causation. Descartes’s <a href="https://plato.stanford.edu/entries/dualism/" target="_blank">dualism</a> left us with the problem of how mental
goings-on could possibly influence physical goings-on (discussed in <a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert.html" target="_blank">Part 1</a>). The whole point of
positing the mental realm was to free our immaterial thoughts from physical
determinism, but this does not explain how those immaterial thoughts can then
push material stuff around.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The solution is to realise that thoughts
are not immaterial. They are entailed by <i style="mso-bidi-font-style: normal;"><a href="https://osf.io/preprints/psyarxiv/dfkrv" target="_blank">meaningful patterns</a> of neural activity</i>. Now, you might say that that proves Sapolsky’s
point – that what happens in the brain is just determined by these physical
patterns. But in fact the workings of the brain are not sensitive to the
details of those patterns – they are sensitive to <i style="mso-bidi-font-style: normal;">what the patterns mean</i>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The elements of cognition are not neural
firings. They’re <a href="https://www.nature.com/articles/s41583-021-00448-6" target="_blank">higher-order patterns</a> of neural activation that represent
beliefs and desires and goals and possible actions. Those patterns are “multiply
realisable” – they are macrostates that can be realised by many different
microstates. The brain is configured to be causally sensitive to these
high-level macrostates – the details of the microstates, in contrast, are
arbitrary and incidental. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, we really do think. Cognition is not an
epiphenomenon. Mental states are instantiated by some neural states but cannot
be identified with or reduced to them. Neural states have causal influence on
the system by virtue of what they mean. Conversely, having a thought, with some
particular “content” has causal efficacy in the system because of this physical
instantiation. No magic required. Just meaning.</span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-64173165868415859112024-01-12T05:55:00.000-08:002024-01-12T05:55:34.926-08:00Undetermined - a response to Robert Sapolsky. Part 3 - Where do intentions come from?<span lang="EN-GB">In his book <a href="https://mitpressbookstore.mit.edu/book/9780525560975" target="_blank"><i style="mso-bidi-font-style: normal;">Determined</i></a>, Robert Sapolsky argues that our intentions arise in a
completely deterministic fashion from the combined effects of all the prior
causes that have acted on us, right up to the moment of action. He contends (i)
that our intentions determine what we do, and (ii) that we have no control over
their formation – they just appear when we are confronted with each successive
situation we encounter. Referring to a classic turn-back-the-clock kind of
thought experiment, he says:</span>
<p class="Default"> </p>
<p class="MsoNormal"><span lang="EN-GB" style="font-size: 10.5pt;">But no matter how
fervent, even desperate, you are, </span><i><span lang="EN-GB" style="font-size: 10.5pt; mso-bidi-font-family: "Caslon 540 LT Std";">you can’t successfully wish
to have wished for a different intent</span></i><span lang="EN-GB" style="font-size: 10.5pt; mso-bidi-font-family: "Caslon 540 LT Std";">. And you
can’t meta your way out— you can’t successfully wish for the tools (say, more
self- discipline) that will make you better at successfully wishing what you
wish for. None of us can. (page 46, original emphasis)<i></i></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Here, Sapolsky seems to be arguing for <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">psychological
determinism</i></b>. Your behavior at any moment is fully determined by the
sets of reasons that you bring to the situation. So, <a href="https://en.wikipedia.org/wiki/On_the_Freedom_of_the_Will" target="_blank">echoing</a> Arthur
<a href="https://en.wikipedia.org/wiki/Arthur_Schopenhauer" target="_blank">Schopenhauer</a>, you <i style="mso-bidi-font-style: normal;">can </i>(indeed you <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">must!</i></b>)<i style="mso-bidi-font-style: normal;"> </i>“do what you want”, but you can’t “want
what you want”. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">In
a chapter entitled “Where Does Intent Come From?”, Sapolsky catalogues all the prior
causes flowing seamlessly into each other:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">So on and so
on. Each moment flowing from all that came before. And whether it’s the smell
of a room, what happened to you when you were a fetus, or what was up with your
ancestors in the year 1500, all are things that you couldn’t control.</span><span style="color: black; font-family: "Caslon 540 LT Std","serif"; font-size: 6.0pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"> </span><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">A seamless stream of influences
that, as said at the beginning, precludes being able to shoehorn in this thing
called free will that is supposedly in the brain but not of it. (Page 80)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Note first, as discussed in <a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert_28.html" target="_blank">Part 2</a> of this
series, that the studies supposedly demonstrating these influences are not, in
my view, reliable (at all) and give a misleading impression of the strength of
these effects. And note also the dualist framing, pointed out in <a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert.html">Part 1</a> of this
series, requiring free will to be “in the brain but not of it”. He continues in
a similar vein:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">In order to
prove there’s free will, you have to show that some behavior just happened out
of thin air in the sense of considering all these biological precursors. (page
83)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For Sapolsky, you are thus simply the
product of all the passive influences that have moulded you to be the person
you are. The way you are currently constituted then fully determines your
actions <i style="mso-bidi-font-style: normal;">in every possible scenario you
might encounter</i>, without you, as a whole self, really being involved in
that process – specifically, none of what happens is <i style="mso-bidi-font-style: normal;">up to you</i>. You are, in essence, pushed around by your own reasons,
none of which you had any hand in choosing. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As we will see, this kind of psychological
determinism reduces to the claim that all these prior influences have
collectively caused <i style="mso-bidi-font-style: normal;">your physical brain</i>
to be configured in the way that it is, which then <i style="mso-bidi-font-style: normal;">physically necessitates</i> subsequent states, resulting in this
conclusion:<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">It is why it is
anything but an absurdly high bar or straw man to say that free will can exist
only if neurons’ actions are completely uninfluenced by all the uncontrollable
factors that came before. It’s the only requirement there can be, because all
that came before, with its varying flavors of uncontrollable luck, is what came
to </span><i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">constitute </span></i><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";">you. This is how you became you.
(page 84)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky takes issue with compatibilist
arguments that claim that even if you have no choice or control over what you
do right now – because of the way your brain is configured, which embodies all
kinds of policies and heuristics that will inform your current intentions – nevertheless
you can be held responsible <i style="mso-bidi-font-style: normal;">for having
those policies and heuristics</i>. Here, I agree with him – it seems incoherent
of compatibilists to admit that at any given moment we have no real choice
(because determinism holds), but then claim that in the past we could have made
choices of what policies to adopt, which we can now be held responsible for. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, Sapolsky’s own view –
diametrically opposed to the compatibilist position – is entirely circular. The
logic is that, because you never had control, you can never have control:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="color: black; font-family: "Caslon 540 LT Std","serif"; mso-ansi-language: EN-US; mso-bidi-font-family: "Caslon 540 LT Std";"> </span></p>
<p class="MsoNormal"><span style="font-family: "Caslon 540 LT Std","serif"; font-size: 10.5pt; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">all we are is
the history of our biology, over which we had no control, and of its
interaction with environments, over which we also had no control, creating who
we are in the moment. (page 85)</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">He argues that because choice doesn’t exist
in any instant, then you – as a person, a self – could have had no control over
your own dispositions. The argument thus rests on the thing it’s trying to
prove. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If, instead, choice does exist in any
moment, and you do have causal power over your own behavior, including the
adoption of policies and heuristics that will inform future actions, then this
view of you being an automaton passively shaped by forces outside your control
is undermined. In its place we get a picture – and a naturalised scientific
framework – of organisms steering their own course through the world, as best
they can, deciding what to do in any moment, based on what they have learned
from past experiences, in the context of their ongoing plans and commitments
and agendas. In fact, it is precisely this combination of historicity and
future-directedness that constitutes being a self, with continuity through time.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Where
do our intentions come from?</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Our intentions do not, in fact, just follow
automatically from how we are currently configured and then control what we do,
like commands to be executed in a computer. They are <i style="mso-bidi-font-style: normal;">the outcome</i> of our decision-making processes. That’s the point of
decision-making – to figure out what we should do. Once we achieve that, it
becomes our intention. This could be an immediate motor action, like moving our
hand to switch on a light. Or it could be a longer-term project, like intending
to finish university – a <i style="mso-bidi-font-style: normal;">goal</i> we
adopt, which then provides context for our future and ongoing <i style="mso-bidi-font-style: normal;">activities</i>, which in turn provide
context for our specific <i style="mso-bidi-font-style: normal;">actions</i>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We don’t just go around reacting to stimuli
in isolated instants. We manage our behavior proactively through time. We
pursue agendas, we adopt policies and heuristics, we make plans and
commitments, and engage in projects with long-term goals. Choosing an action is
really choosing <i style="mso-bidi-font-style: normal;">an objective</i> – a
desired future state of the world (including the state of our selves). We make
the future what we want it to be – that is the point of action. But not just
the immediate next time-point – we work to make things in the far future how
we’d like them to be. This longer-term view of the management of behavior
through time gives a better perspective on where our goals and intentions come
from. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Achieving our goals requires sustained
action – we usually have to carry out some series of activities over some period
of time. If I have the goal of eating, I may have to spend time cooking a meal.
For this activity to achieve my goal, <i style="mso-bidi-font-style: normal;">I
have to keep doing it</i>. So choosing the goal to cook dinner, based on the
motivation of being hungry, constrains and informs <i style="mso-bidi-font-style: normal;">what I will intend to do</i> over the course of whatever period of time
it takes to do that task. I may intend to chop up an onion, and sauté some
chicken, and make a lovely little soy and ginger sauce, and so on. Those
intentions thus come from me having adopted this goal and from me thinking
about the steps I need to take to achieve it. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Similarly, if I decided to play a round of
golf, I would have, in the process, <i style="mso-bidi-font-style: normal;">decided
to intend</i> to put the little ball in the hole. That intention came from me.
When we decide to do something, a whole bunch of intentions have to come along
in order to achieve that. So it’s not the case that while we can do what we
want, we can’t want what we want. Our reasons don’t just reflect the
pre-configuration of our brains in isolated instants. We come to those reasons <i style="mso-bidi-font-style: normal;">by reasoning</i>.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Those processes of decision-making must
take into account our current state, the state of the world, the states we
would ideally like both our selves and the world to be in, and then (i) suggest,
and (ii) evaluate, options for action to find the one most likely to further
the likelihood of those desired states. Now, you might argue that we don’t have
control over the middle bit – the states we would ideally like our selves to be
in. And, at a general and low level, that’s true – we’re wired to want to be
well fed and watered, and warm and safe and loved and even entertained and
fulfilled, and so on. Most fundamentally, we’re wired to want to survive. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But those kinds of basic evolutionary
drives are not sufficient to determine our behavior. They are too general and
context-independent. The same is true for the broad tunings of decision-making
parameters that are reflected in what we call personality traits. We can’t rely
on these general drives and tunings to tell us the best thing to do in any
given situation. We have to be able to assess the particular situation we’re in
and set more specific, context-appropriate goals, and select actions to achieve
them. This entails <i style="mso-bidi-font-style: normal;">cognition</i>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Why
we need cognition</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Cognition, roughly speaking, means using
information to solve problems – usually to manage behavior over changeable
environments. In some cases, a lot of the work of cognition is pre-done by
evolution. For example, the biochemical configuration of a bacterium may
effectively embody adaptive control policies, such as the tendency to move in
certain directions, based on information acquired by receptor proteins about
various substance that are out in the world. These kinds of systems can be
reasonably complex – able to integrate multiple signals at once and mount a
response that depends on many other contextual factors, including the recent
history of the individual bacterium itself. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Even simple behaviors like chemotaxis thus
entail holistic and integrative <a href="https://www.mdpi.com/1099-4300/24/4/472" target="_blank">system-level control</a>, aimed at enacting the
optimal response. But what is the optimal response? In the bacterium, there is
a manageable number of variables at play. Even if the context-dependent
interactions are complicated, they’re not unworkably complicated. Evolution can
pre-code a system of contingencies and context-dependent relations that are
sufficient to deal with most scenarios that the organism will encounter, based
on the limited range of scenarios its ancestors encountered. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That strategy has limits, however. It
certainly won’t do for us. Humanity’s superpower – our whole evolutionary
schtick – is cognitive flexibility. We don’t have hard-coded responses to every
situation – we couldn’t have. There isn’t enough information in our genomes or
our brains to pre-code defined responses to every kind of situation we may
encounter. There are too many variables at play, too many relations to
consider, too many goals to manage. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The solution is to decouple inputs from immediate
action and instead gather information about what is out in the world and submit
it to a central system, where it can all be considered, in the light of our
stored knowledge about the world, and our current and ongoing goals, in order
to try to decide on the best course of action to globally optimise over a host
of variables all at once. In other words, <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">we need to think</i></b>.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In some cases, there may be one clear
optimal course of action. But in many cases, there may be several, or none. The
organism has to take in all kinds of sensory data, do its best to infer the
causes of those data (i.e., infer what is out in the world), link that to its
imperfect and incomplete knowledge, in order to update its model of the world
with varying degrees of certainty attached to different elements, predict the
outcomes and utility of possible actions, while the world and other agents are
changing too, all while trying to satisfy multiple goals at once. </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman"; mso-fareast-font-family: "Times New Roman";">That <i style="mso-bidi-font-style: normal;">just is</i>
the organism deciding what to do, in real-time.</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There seem to be two ways to take Sapolsky’s
counter-argument, in relation to these processes of decision-making. Either, as
put by my student Henry Potter: (i) “</span><span style="background: white; color: #242424; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman"; mso-fareast-font-family: "Times New Roman";">all of the system’s prior influences
have hammered into it a neural and biochemical configuration that essentially
embodies a look-up table for which action to perform under different
circumstances. There is therefore no decision-making <i>process</i> going
on. In effect, the decision is already made, it just needs to be ‘realised’ or
‘enacted’.” Or: (ii) processes of decision-making do have to happen in each new
scenario, but they always have only one possible outcome – that is, they
proceed algorithmically and deterministically. </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman"; mso-fareast-font-family: "Times New Roman";"></span></p>
<p class="MsoNormal" style="background: white; vertical-align: baseline;"><span style="mso-spacerun: yes;"> </span><span lang="EN-GB"></span></p>
<p class="MsoNormal" style="background: white; vertical-align: baseline;"><span lang="EN-GB">The first interpretation seems impossible and I presume is not actually
what Sapolsky has in mind. There is no way to pre-state all the scenarios an
organism might find itself in and all the appropriate actions. But the second
interpretation is no better – or, at least, it’s wildly speculative. </span></p>
<p class="MsoNormal" style="background: white; vertical-align: baseline;"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Resting
psychological determinism on neural and physical determinism</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky seems to be arguing, without
evidence, that all of those activities of reasoning and deciding are algorithmically
deterministic – that there is only ever one possible outcome. This is basically
a behaviorist and mechanistic position. It sees our brains as just one big
(though very complicated) stimulus-response machine. Fundamentally, it denies
that cognition or mental causation is real – that us thinking about what to do
could have any causal influence in this physical system. It says the “contents”
of our mental states don’t really matter – it is only the <i style="mso-bidi-font-style: normal;">vehicles </i>of those states that have causal efficacy in the system.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It takes these cognitive operations as really
<i style="mso-bidi-font-style: normal;">no more than</i> the firings of certain
neural circuits, which were in fact inevitable, at every moment in this
sequence of events. This rests on the idea that the current configuration of
our nervous system (which is the product of all those prior causes), plus the
current incoming stimuli, deterministically result in a single next state of
our nervous system, entailing some specific action. There is no choice. In
every situation, all these antecedent causes will necessitate just one
subsequent outcome. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There are two ways in which these processes
could be algorithmically deterministic. The most obvious one is if the substrates
they are instantiated in are physically deterministic. Then the whole argument
just reduces to physical determinism, and the psychological framing of reasons
and intents becomes an epiphenomenon. This is indeed the argument that many
free-will skeptics make. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, as we will see in Part 4, Sapolsky
himself accepts that isn’t the case. He discusses the evidence that there is both
fundamental indeterminacy in physical systems and pervasive noisiness in neural
systems. So we shouldn’t expect any neurally instantiated process to be fully
deterministic in its physical details. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The determinist’s move to escape from this
challenge is, ironically, a determinedly <i>anti-reductive</i> one. It relies on the
idea that all that noisiness of neural components and their physical
micro-constituents is coarse-grained over – filtered or averaged out over the
large numbers of components of the system. Then you could get an <i style="mso-bidi-font-style: normal;">emergently</i> deterministic outcome at the
macro-level, with the noise simply evaporating. This would of course depend on
the structure of the system – on the way that it is organised. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This move is doubly ironic, because, as I
will explore in Part 4, it is precisely these factors of indeterminacy and
emergence and organisation that enable organisms themselves to come to be in
charge of what happens. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"><br /></span></p><p class="MsoNormal"><span lang="EN-GB"><br /></span></p><p class="MsoNormal"><span lang="EN-GB"><br /></span></p><p class="MsoNormal"><span lang="EN-GB"><br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"><a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert.html" target="_blank">Part 1</a>: A tale of two neuroscientists</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"><a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert_28.html" target="_blank">Part 2</a>: Assessing the scientific evidence</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-40324873827193911662023-12-28T03:26:00.000-08:002023-12-28T03:26:34.711-08:00Undetermined - a response to Robert Sapolsky. Part 2 - assessing the scientific evidence<p><span style="font-size: medium;">In <span style="color: black;"><a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert.html" target="_blank">Part 1</a> of this series, I explored the different philosophical premises that Robert Sapolsky and I bring to the question of free will, in our respective books, <a href="https://mitpressbookstore.mit.edu/book/9780525560975" target="_blank">Determined</a> and <a href="https://press.princeton.edu/books/hardcover/9780691226231/free-agents" target="_blank">Free Agents</a>. Here, I will examine the scientific evidence that Sapolsky marshals to make his argument that all our decisions are fully determined. <br /></span></span>
</p><p class="Default"><span style="font-size: medium;"><b><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">Part
2</span></b></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><b><span lang="EN-GB">No,
but yeah, but no – assessing the scientific evidence</span></b></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Sapolsky presents an array of experimental
evidence from studies of various kinds to support his claim that we are <i>completely driven</i> by all the causal
factors in our past or intervening on us in the present. The word study appears
163 times in the text, in fact, and it felt a bit like being pummeled into
submission at times. I’m all for providing experimental evidence to support
one’s claims, but in this case, much of the supposed evidence is completely
unreliable. The fields that are cited the most include social psychology,
especially social “priming” experiments, candidate gene association studies,
and certain kinds of neuroimaging studies. All of these suffer from very well
documented <span style="color: black;"><a href="https://www.nature.com/articles/d41586-019-01307-2" target="_blank">methodological problems</a>, known collectively as “<a href="https://replicationindex.com/2015/01/24/qrps/" target="_blank">questionable research practices</a>”. </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">The problems stem from small samples,
poorly defined hypotheses, excess researcher degrees of freedom (lots of ways
to analyse the data), post hoc analyses, covariate mining (slicing the data in
lots of ways to look for something significant somewhere), p-hacking, failure
to correct for multiple tests, lack of independent replication, and the huge
issue of publication bias. Collectively, these practices are empirically demonstrated
to produce literatures composed almost entirely of <a href="https://doi.org/10.1371/journal.pmed.0020124" target="_blank">spurious findings</a> –
apparently significant associations that really are just statistical blips.
Because we only hear about the “positive” results, these bodies of literature
can collectively give the impression of robustness and consistency, when in
fact this results from biased reporting. <span> </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Here are a few examples from the text:</span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><i><span lang="EN-GB">In one highly cited study, subjects rated their
opinions about various sociopolitical topics (e.g., “On a scale of 1 to 10, how
much do you agree with this statement?”). And if subjects were sitting in a
room with a disgusting smell (versus a neutral one), the average level of
warmth both conservatives and liberals reported for gay men decreased. Sure,
you think— you’d feel less warmth for anyone if you’re gagging. However, the
effect was specific to gay men, with no change in warmth toward lesbians, the
elderly, or African Americans. (Page 47)</span></i></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">The study is presented as solid and
reliable (with the implication that it also has some relevance for real-world
behavior). But you should ask if the supposedly interesting “specificity” of
the result was actually an unhypothesised and spurious finding from slicing the
data multiple ways, and you should also ask if it has ever been replicated. Moreover,
you can be sure that no one has read the results of other similar studies that
may have been done that did not produce any such “positive” finding, because
they never get published. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">The whole field of <a href="https://www.nature.com/articles/d41586-019-03755-2 " target="_blank">social priming</a> has been
called into question as literally the poster child for the replication crisis.
Even Daniel Kahneman, who was a <a href="https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow" target="_blank">huge proponent</a> of this kind of work, has more
recently had to concede that it is <a href="https://replicationindex.com/2017/02/02/reconstruction-of-a-train-wreck-how-priming-research-went-of-the-rails/" target="_blank">not robust</a> and has called on the field to
face up to this fact.<span> </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Here’s another example:</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="Default"><span style="font-size: medium;"><i><span style="font-family: Cambria;">What best predicted whether a judge granted someone parole versus </span></i><i><span style="font-family: Cambria;">more jail time? How long it had been
since they had eaten a meal. Appear before the judge soon after she’s had a
meal, and there was roughly 65 percent chance of parole; appear a few hours
after a meal, and there was close to a 0 percent chance. (Page 106). </span></i></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria;"> </span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">This
particular study is trotted out frequently, again to show how much our behavior
– even on <i>really important decisions</i>
such as this, made by people literally selected to be professional
decision-makers – is driven by subconscious biological states, such as how
hungry we are. This very famous example appears to <a href="https://www.cambridge.org/core/journals/judgment-and-decision-making/article/irrational-hungry-judge-effect-revisited-simulations-reveal-that-the-magnitude-of-the-effect-is-overestimated/61CE825D4DC137675BB9CAD04571AE58" target="_blank">actually be driven</a> by the
fact that defendants without representation, who are less likely to get parole,
tend to have their cases scheduled right before lunch (because they’re quick). </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">The same unfortunate trend is evident
across many other types of study cited. These include ones where people’s
behavior is supposedly changed by exposure to various neural signaling
molecules. For example:</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="Default"><span style="font-size: medium;"><i><span style="font-family: Cambria;">Boost your oxytocin levels experimentally, and you’re more likely
to be charitable and trusting in a competitive game. (page 54). </span></i></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Notice first how this is presented not as a
particular finding from a particular study, but <b>simply as a fact</b> with general
predictive validity. There is a veritable cottage industry of studies involving
spraying oxytocin up people’s noses and testing them on all kinds of behaviors.
Again, the methods and the <a href="https://www.jstor.org/stable/44281952" target="_blank">findings</a> have been shown to be <a href="https://journals.sagepub.com/doi/10.1177/1745691620921525" target="_blank">unreliable</a>. </span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">On the role of genetics in our behavior:</span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><i><span lang="EN-GB">Consider the neurotransmitter serotonin— differing
profiles of serotonin signaling among people </span></i><span lang="EN-GB">[KM: due to different genetics] <i>help explain individual differences related to mood, levels of arousal,
tendency toward compulsive behavior, ruminative thoughts, and reactive
aggression. (Page 72).</i></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">This section refers to results from
so-called <a href="https://www.sciencedirect.com/science/article/pii/S0959438812001146" target="_blank">candidate gene association studies</a>. Again, this methodology is no
longer used because it is now well known to produce spurious findings, which
have failed to replicate in much larger, much more systematic studies. The gene
encoding the serotonin transporter, referenced here, is probably the <a href="https://slatestarcodex.com/2019/05/07/5-httlpr-a-pointed-review/" target="_blank">most notorious example</a> of this untrustworthy literature. </span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria;"> </span></span></p>
<p class="Default"><span style="font-size: medium;"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">Finally, many neuroimaging studies are appealed
to, which can seem to bolster the findings from social psychology experiments
by referring to different parts of the brain “lighting up” differently under
different conditions across different groups. The tortured phrasing of that sentence
is intended to highlight the large number of variables and possible interactions
in such studies that researchers can mine for significant findings. Here’s one
illustrative example, with a typically convoluted and arbitrary set of
interactions:</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><i><span lang="EN-GB">In another neuroimaging study, performance on a
frontal task declined in subjects primed with pictures of spiders (versus
birds); among African American subjects, the more of a history of
discrimination, the more spiders activated the vmPFC and the more performance
declined.</span></i></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><i><span lang="EN-GB"> </span></i></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Again, recent work has highlighted how
unreliable these kinds of studies are. In particular, studies that look across
the whole brain for any kinds of differences between test groups are typically statistically
“under-powered” by two to three <i>orders of
magnitude</i>. That is, many of them have samples in the tens, when, to be
reliable, they would need samples in the <i><a href="https://www.nature.com/articles/s41586-022-04492-9" target="_blank">thousands</a>
or <a href="https://www.biorxiv.org/content/10.1101/2023.09.21.558661v1 " target="_blank">tens of thousands</a></i>. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">So, overall, the evidence base that
Sapolsky draws on to emphasise the potency of all these supposed determinants
of our behavior is, to put it bluntly, completely untrustworthy. This isn’t
just my opinion. This is the <a href="https://www.nature.com/articles/nrn3475 " target="_blank">opinion of researchers</a> in these <a href="https://pubmed.ncbi.nlm.nih.gov/33954258/" target="_blank">fields themselves</a>,
many of which, like human genetics, have completely overhauled the way they
work to overcome the limitations of these kinds of “artisanal” studies. <span> </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><b><span lang="EN-GB">But
yeah…</span></b></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">That was the “No” part. But there is a “but
yeah” to follow. Even though the types of studies that Sapolsky relies on are
unreliable and unconvincing, this doesn’t mean such effects don’t exist. These
factors are probably not as individually potent as he suggests, but it is still
absolutely true that all kinds of prior causes influence our behavior. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">For example, the fact that we can’t
identify strong associations between individual genes and individual
personality traits does not undermine the very strong evidence that such traits
are partly heritable. (That is, that a sizeable proportion of the variance
observed in such traits across the population can be attributed
to genetic variation generally). It just means the relationship between
genotypes and phenotypes is <a href="https://press.princeton.edu/books/paperback/9780691204154/innate" target="_blank">highly complex</a>. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">The same is true for neuroimaging
experiments – the failure to associate complex psychological traits with
variation in structure or function of isolated brain areas does not undermine
the idea that such traits are associated with <i>some differences</i> in the brain. Again, it’s just highly complex. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">And while most of the social priming
literature is clearly artifactual, that doesn’t mean that we are not affected
in the real world by all kinds of factors in the environment, some of which we
may not be aware of.<span> </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">All of these factors constrain (or inform) our
behavior. However, if the existence of such factors is supposed to be a
challenge to the idea of free will, it is only a challenge to an <b>absolutist
form</b>. Some argue that having free will requires being <i>absolutely free</i> from the influence of any prior cause whatsoever. A
quick scratch beneath the surface reveals how incoherent this notion is. A
being that was free from all prior causes would have no reason to do anything, no
evolved nature to begin with, no responsiveness to the environment, and neither
future-directed goals nor memories of past experience to guide its behavior. It
would just be a random-behavior-generator.</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">It would not in fact be a self with any
continuity through time – and continuity through time is the very thing that
defines selves. For any living organism, being a self entails doing work to
constrain its component parts and processes to remain organised in the
particular way that defines that individual. This is just as true at a
psychological level as it is at a physical level. It is precisely our
individual personalities and character traits, our memories, our ongoing
projects and commitments, our habits and attitudes and policies that
collectively make us who we are. Indeed, when people start acting “out of
character”, it is often a sign of neurological or psychiatric illness. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">So, we don’t have absolute freedom – we
wouldn’t be ourselves if we did. What we have are <b><i>degrees of freedom</i></b> – some
set of options available to us, informed by all these past and current factors.
These influences only become a threat to a more reasonable conception of free
will if they are taken to be <i>complete
determinants</i> of what we do at any moment – if they reduce our degrees of
freedom to zero. This is what Sapolsky asserts, but without evidence.</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><b><span lang="EN-GB">But
no…</span></b></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">In discussing these various influences,
stretching backwards over different timescales, Sapolsky is careful to state
that each one of them is only an influence and not an absolute determinant by
itself. That is good, because if any one of them (say your genetics) were
determinative, it would rule out any role for any of the others (like your
experiences).<span> </span></span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">But he does assert, completely
speculatively and without evidence, that <b><i>all of them collectively</i></b> do
completely determine our behavior, precluding the possibility of the organism
itself playing a role in settling what happens. He claims that while we don’t
yet have all the details, “we already know enough” to say there is not the smallest
gap left in which free will could reside. (Note that this also means no further
biological causes can be admitted, since we’re full up of causes already). </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">As an aside, but perhaps an important one,
the use of the words “causes” in these kinds of discussions is highly loaded
and likely to lead our thinking astray. It suggests a chain of <i>necessitating</i> events, deterministically
driving behavior. And it seems to require the mythical beast – an “<a href="https://en.wikipedia.org/wiki/Cosmological_argument" target="_blank">uncaused cause</a>” – to arise somewhere to break this inexorable chain. But if you replace
“causes” with “influences”, you get a much more open, flexible, ecumenical
picture that much better captures the real nature of what’s going on. </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">Sapolsky doesn’t do that, however. His view
is that all these influences collectively determine what we do at every moment.
Clearly, this goes completely against the phenomenology of our everyday
experience. It seems, most of the time, that we are in fact deciding what to
do, that we do have options and we do choose between them, even if that is
within a constrained set of possibilities. To assert otherwise is thus truly an
extraordinary claim, which should be accompanied by extraordinary evidence. In
the absence of any such evidence, Sapolsky relies on a series of arguments to
try and make his case. One of those arguments – the central one, in fact – is
that while we can do what we intend, our intentions are not up to us.</span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB"> </span></span></p>
<p class="MsoNormal"><span style="font-size: medium;"><span lang="EN-GB">In Part 3, I will examine why that argument
misses its mark.</span></span></p>
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{page:WordSection1;}</font></style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-88392833424782608372023-12-20T10:57:00.000-08:002023-12-28T03:28:55.195-08:00Undetermined - a response to Robert Sapolsky. Part 1 - a tale of two neuroscientists<span lang="EN-GB">Free will is in the air. Among
neuroscientists at least, the question of whether we are in control of our
actions has been attracting renewed attention of late, driven in large part by
the successes of the field in laying bare the neural machinery of behaviour. It’s
thus not a total coincidence that two books by neuroscientists on this topic – <a href="https://mitpressbookstore.mit.edu/book/9780525560975" target="_blank"><i style="mso-bidi-font-style: normal;">Determined</i></a>, by Robert Sapolsky, and <i style="mso-bidi-font-style: normal;"><a href="https://press.princeton.edu/books/hardcover/9780691226231/free-agents" target="_blank">Free Agents</a></i>, by yours truly – have been
published so close together (both in October, 2023). What may be more
surprising to readers is that we reach such divergent conclusions on the topic.
</span>
<p class="MsoNormal"><span lang="EN-GB"><br /></span></p><p class="MsoNormal"><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhClZDzQAbE16hwZEYtzWmEabI9LwM6EpcbuT2IWI7vq-l5ybQygjV-oMJlFxz-2RFAQ1e3GYFhhy0T1v-3MhnPNzwqHETYdj-4C7uIBCtsIkK1MulOJlhKEH4Lp0q9HYHuVcgmWHROXYrTI1XZPa9TODKwKXzoiHE2FIRKk0p09v0bqoYDcps0Xb1ct3rA/s1200/Determined%20and%20Free%20Agents.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="771" data-original-width="1200" height="263" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhClZDzQAbE16hwZEYtzWmEabI9LwM6EpcbuT2IWI7vq-l5ybQygjV-oMJlFxz-2RFAQ1e3GYFhhy0T1v-3MhnPNzwqHETYdj-4C7uIBCtsIkK1MulOJlhKEH4Lp0q9HYHuVcgmWHROXYrTI1XZPa9TODKwKXzoiHE2FIRKk0p09v0bqoYDcps0Xb1ct3rA/w409-h263/Determined%20and%20Free%20Agents.png" width="409" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">With thanks to Bill Sullivan<br /></td></tr></tbody></table><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">That we can survey the same evidence and
interpret it so differently may suggest to some that the question of free will
is not really an empirical one at all. Of course many of the issues are
metaphysical, but both Prof. Sapolsky (Sapolsky hereafter) and myself think
that the science of decision-making is at least relevant to these philosophical
discussions. In short, he thinks that science definitively rules out the
possibility of free will. I think it doesn’t. In fact, I think we can construct
a perfectly unproblematic scientific framework that naturalises the concept.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A number of reviews have compared our two
books (including The <a href="https://www.the-tls.co.uk/articles/determined-robert-sapolsky-free-agents-kevin-j-mitchell-book-review-philip-ball/" target="_blank">Times Literary Supplement</a>, <a href="https://www.nature.com/articles/d41586-023-03335-5" target="_blank">Nature</a>, The <a href="https://www.wsj.com/arts-culture/books/determined-and-free-agents-review-no-choice-in-the-matter-39b2e576" target="_blank">Wall Street Journal</a>, <a href="https://undark.org/2023/11/17/book-review-free-will/" target="_blank">Undark</a> magazine, <a href="https://3quarksdaily.com/3quarksdaily/2023/11/sapolsky-vs-mitchell-on-free-will.html" target="_blank">3 Quarks Daily</a>, <a href="https://nautil.us/yes-we-have-free-will-no-we-absolutely-do-not-431904/" target="_blank">Nautilus</a>, and others), and we also had the chance recently to <a href="https://www.youtube.com/watch?v=V9Y1Q8vhX5Y" target="_blank">debate</a> the issue. But there were
many points left unexplored and here I want to respond more directly and more thoroughly
to some of the claims that Sapolsky makes in his book.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Where
we agree</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">First, I should point out numerous areas
where Sapolsky and I agree. A prominent view on free will among philosophers
and those scientists who trouble themselves with the issue is <a href="https://plato.stanford.edu/entries/compatibilism/" target="_blank">compatibilism</a>.
This is the view that <a href="https://en.wikipedia.org/wiki/Determinism" target="_blank">determinism</a> holds (more on what this is taken to mean
below), but that free will can be taken to be compatible with it. Or more
precisely, that the concept of <i style="mso-bidi-font-style: normal;">moral
responsibility</i> can be taken to be compatible with determinism. As espoused
most forcefully by people like philosopher Daniel Dennett, this view accepts
that there is only one possible future, but still argues that agents can be
held responsible for their actions if they are acting for their reasons, even
if they actually never have any choice in what occurs. Both Sapolsky and I find
this view incoherent. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I also think it’s moot, given the evidence
from physics that the universe is <i style="mso-bidi-font-style: normal;">not</i>
in fact deterministic in that fashion. Sapolsky appears to agree with this and
accepts that there is fundamental indeterminacy at the lowest levels. What he
takes this to mean for determinacy at higher levels is a little less clear and
is something I will come back to.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We also agree that there are all kinds of
factors that influence our behaviour. My previous book, <a href="https://press.princeton.edu/books/paperback/9780691204154/innate" target="_blank"><i style="mso-bidi-font-style: normal;">Innate</i></a>, was all about how the wiring of our brains shapes who we
are. We are definitively not born as blank slates, but have our own individual
natures – innate predispositions that derive from our genetics and the way our
brain happened to develop. Both Sapolsky and I agree that these predispositions
affect the way our patterns of behavior emerge throughout our lives. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, I take these effects to be distal,
indirect, and non-exhaustive, which is why I used the word “shapes” rather than
“determines”. As we will see below, one of the main points of disagreement is that
I think of these and other factors as <i style="mso-bidi-font-style: normal;">influences</i>
on our behaviour while Sapolsky sees them as <i style="mso-bidi-font-style: normal;">absolute determinants</i> of it. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Finally, I am very sympathetic with
Sapolsky’s concern for what philosophers call “moral luck”. This is the idea
that many of the things that people do in life – many of the ways in which
their lives turn out – are due to factors over which they had no control and
for which they deserve neither credit nor blame. This includes their natural
endowments – talents, cognitive capacities, personality traits, and so on – as
well as their social circumstances. Where we differ on this point is that I
think it is perfectly possible to take such factors into account in moral or
legal considerations, without having to take an absolutist metaphysical
position that these prior causes preclude <i style="mso-bidi-font-style: normal;">any
capacity of decision-making whatsoever</i> on the part of the individual.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Clearly, then, we see much of the evidence
regarding the nature of the world and the nature of human beings as entities
the same way. Nevertheless, we end up with different conclusions. One
explanation for this could be that we start with different premises, perhaps
implicit or tacit ones. It is thus worth exploring the assumptions and stances
we bring to bear that inform our thinking. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Closet
dualism </span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky rightly criticises the position of
<a href="https://en.wikipedia.org/wiki/Dualism" target="_blank">dualism</a> – the idea, inherited from <a href="https://en.wikipedia.org/wiki/Ren%C3%A9_Descartes" target="_blank">Descartes</a>, that there are two separate kinds
of stuff, physical and mental. Under this view, the mental realm is where we
make decisions, thus freeing us from the confines of physical determinism. This
implies the existence of a “ghost in the machine” – an immaterial self that
somehow inhabits your brain and body and pushes things around. Sapolsky derides
this view as unscientific, which it obviously is, and rightly says that it
provides no solution to the problem of free will – at least none that any
scientist committed to the idea of physicalism (basically, no magic allowed)
should accept. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, his own position is <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">dualist
through and through</i></b>. Right from the get-go, he frames the idea that a
human being – as a whole entity – could be a cause of something as ludicrous
and supernatural. On page 2, he writes, in relation to any behavior, that we
can ask:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="Pa28" style="text-align: justify; text-justify: inter-ideograph;"><i style="mso-bidi-font-style: normal;"><span style="font-family: Cambria; font-size: 11.0pt; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">Why
did that behavior occur? If you believe that turtles can float in the air, the
answer is that it just happened, that there was no cause besides that person
having simply decided to create that behavior. Science has recently provided a
much more accurate answer, and when I say “recently,” I mean in the last few
centuries. The answer is that the behavior happened because something that preceded
it caused it to happen.</span></i></p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;"> </span></i></p>
<p class="MsoNormal"><span lang="EN-GB">I guess I’d better explain the reference to
turtles! This refers to an anecdote about a woman arguing with <a href="https://en.wikipedia.org/wiki/William_James" target="_blank">William James</a>
that he had his cosmology all wrong and the earth really rested on the back of
a turtle. When he asked her what the turtle rested on, she said “another
turtle”. And when he asked the inevitable question of what <i style="mso-bidi-font-style: normal;">that</i> turtle rested on, she replied: “It’s no use, Professor James.
It’s turtles all the way down!” I gather Sapolsky is sympathising with the
woman in the story, in the sense that every cause that we might give for an
action inevitably has the same kind of regress of prior causes that it “rests on”.
(There is also a hint here of the reductionist instincts that permeate the book
– looking down instead of up). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The framing of the issues in the cited
paragraph is firmly, though implicitly, dualist. First, there is the odd idea
that a behavior occurring because the person “simply” decided to do something is
basically identical to it having “just happened”, as if for no reason. But the
whole point is that we can do things for our reasons, not at random. And as we
will see, there is nothing “simple” about our decision-making processes. Nor is
there any reason, a priori, to rule out the possibility of <i style="mso-bidi-font-style: normal;">the person themselves</i> being a cause of things – that’s the very
question under debate. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Then there’s the implication that any such
causation would require a miracle (the floating turtle) and is thus patently
absurd. This only follows from the dualist position that when we say something
is up to you, the “you” must be some kind of immaterial soul or ghost in the
machine – as opposed to just your holistic self. Again, this rules out from the
get-go a more naturalistic explanation – the very thing we’re after. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And finally, there is the assertion that
science can replace – and indeed has replaced – such superstitious absurdities
with the <i style="mso-bidi-font-style: normal;">real explanation</i>, which is
couched in a linear chain of inexorable and inevitable causes of the
respectable sciencey kind. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These themes are repeated throughout the
book. On multiple occasions, Sapolsky implies that if biological factors are at
work, these can’t provide the explanation or the vehicle for any real kind of
free will, just by definition. </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;">Each prior influence flows without a break from the
effects of the influences before. As such, there’s no point in the sequence
where you can insert a freedom of will that will be in that biological world
but not of it. (Page 46)</span></i></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The image of “inserting” a freedom of the
will into the biological world, so that it is “in it, but not <i style="mso-bidi-font-style: normal;">of it</i>” is a clear articulation of a
dualist position. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Again, on page 83:</span></p>
<p class="Default"><i style="mso-bidi-font-style: normal;"><span style="font-family: Cambria; font-size: 11.0pt; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></i></p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;">In order to prove there’s free will, you have to show
that some behavior just happened out of thin air in the sense of considering
all these biological precursors.</span></i></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Why “out of thin air”, as if this requires
magic? This just <i style="mso-bidi-font-style: normal;">assumes</i> that the
individual cannot be a cause of their own behavior – exactly the question at
hand. If you set up the problem such that the only solution that would meet the
threshold of free will is one involving this kind of supernatural interference
in the normal run of physical causation, then of course you will never be
satisfied by any naturalistic claim that explicates behavioural control as an
evolved capacity of living organisms. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">God
of the gaps</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This dualistic framing is also evident in
Sapolsky’s repeated assertion that the only place where “you” can reside is in
the gaps in our current knowledge of biology. Science is seen as revealing <i style="mso-bidi-font-style: normal;">the real causes</i> of what happens, at
deeper and deeper mechanistic levels. As this occurs, there seems less and less
for <i style="mso-bidi-font-style: normal;">you</i> to do, less and less room for
any kind of holistic or top-down causation. All the causal power is located at
the lowest levels (whatever they are taken to be) and the notion of
higher-order causation by the self, as a whole entity, is eliminated in the
process. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is, of course, how atheist scholars
characterise religion, as having to stage strategic retreats with every advance
of science, taking refuge in whatever mysteries remain – hence, the god of the
gaps. The implication is that science will eventually close all these gaps and
the need to invoke a deity to explain anything at all will disappear. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sapolsky’s eliminative reductionism
similarly seeks a full causal explanation of behavior in the biological
mechanisms that science is laying bare. This is thus the flip side of his
implicit dualism – if the only thing that would be <i style="mso-bidi-font-style: normal;">real</i> free will is control by an immaterial self, apparently without
involving any mechanism, then of course the more mechanisms biology reveals,
the less room there is for the self to wield any influence, or even to exist at
all. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">My own position is one of non-reductive
materialism. We don’t need to invoke any supernatural forces to explain how
organisms can control their actions and how agents can have causal power in the
world. There are plenty of resources available to us in the various sciences of
systems that give perfectly naturalised concepts of holistic or top-down
causation. Sapolsky considers some of these ideas in later chapters, but in a
disappointingly dismissive way that, in my view, fails to fully engage with
them. As such, I think he misses the very ideas we need to understand how
causal agency can exist. It may be turtles all the way down, but it’s not
turtles all the way up.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">“Don’t
look up!”</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In eliminating the possibility of the whole
self being a causal entity, Sapolsky offers a different challenge to proponents
of free will, one that looks down, instead of up. In the first chapter, for
example, he describes a scenario where a man pulls the trigger of a gun. He
describes the set of causes of this event as the series of nerve impulses,
working backwards from the ones that caused his trigger finger to contract, to
the ones that caused those neurons to fire, and so on. (Note the purely
mechanistic, driving framing – more on that later). He then says: <span style="mso-spacerun: yes;"> </span></span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="MsoNormal"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB" style="font-size: 11.0pt;">Here’s the challenge to a free willer: Find me the
neuron that started this process in this man’s brain, the neuron that had an
action potential for no reason, where no neuron spoke to it just before. (page
14)</span></i></p>
<p class="MsoNormal"><span lang="EN-GB" style="font-size: 11.0pt;"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The idea is that if you could show him “a
neuron being a causeless cause in this sense”, then you would have proven free
will. This just strikes me as such an odd set-up. Why would some neuron firing
at random and thereby causing a behavior constitute an instance of free will?
Why look for such a reductive explanation, at the level of specific neurons? We
know that’s not how the brain works. He goes on to say:</span></p>
<p class="Default"><span style="font-family: Cambria; font-size: 11.0pt; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="Default"><i style="mso-bidi-font-style: normal;"><span style="font-family: Cambria; font-size: 11.0pt; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">The prominent compatibilist philosopher Alfred Mele of Florida
State University emphatically feels that requiring something like that of free
will is setting the bar “absurdly high.” (page 15)</span></i></p>
<p class="Default"><span style="font-family: Cambria; font-size: 11.0pt; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">I disagree. It’s not that the bar is too
high. It’s just the wrong bar. We’re on the wrong playground. What he’s asking
for would not in fact satisfy anyone’s concept of free will, including his own
(because it would not give any causal power to the individual). He’s looking
down when he should be looking up (but not up so far that the explanation has
to sit somehow outside our heads in a ghostly self). </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">So, we differ in some of our philosophical
stances in ways that provide at least some explanation for why our
interpretation of the scientific evidence also differs so profoundly. </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">As to that evidence itself, most reviewers
have taken Sapolsky’s presentation of it as a fair assessment of the profound influence
that a whole range of biological factors can have on our behavior. Here, I am
in an odd position: I agree that such factors can influence our behavior – of course
they can – but I find the actual evidence that Sapolsky marshals to support
this notion to be highly flawed. Indeed, the types of studies that he leans on
to make this argument are literally ones that I (and many others) use as prime examples
in lectures about irreproducible science and the “<a href="https://en.wikipedia.org/wiki/Replication_crisis" target="_blank">replication crisis</a>”. </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"> </span></p>
<p class="Default"><span style="font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">More on that in <a href="http://www.wiringthebrain.com/2023/12/undetermined-response-to-robert_28.html" target="_blank">Part 2</a>.</span></p>
<p><style>@font-face
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-6370547093461105562023-09-18T04:54:00.002-07:002023-09-18T05:01:14.937-07:00What questions should a real theory of consciousness encompass? <span lang="EN-GB">Well, now! The consciousness field is all
atwitter! <a href="https://psyarxiv.com/zsr78/">A letter</a> has been published, with 124 signatories, claiming that one
prominent “theory of consciousness” – the <a href="https://en.wikipedia.org/wiki/Integrated_information_theory">Integrated Information Theory</a>
proposed and developed by Giulio Tononi, Christof Koch and colleagues over
several years – is “pseudoscience”. That’s a serious charge to level in print,
and one that I presume the authors of the letter did not make lightly. </span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The letter was a response to some of the
media coverage around the COGITATE study – an adversarial collaboration which
purports to test the predictions of several theories of consciousness in an
open and fair way. (You can see <a href="https://psyarxiv.com/28z3y">here</a>, from Hakwan Lau, some commentary on
whether it is actually designed and executed appropriately to achieve that). The letter
seems to reflect the growing exasperation of some researchers in the field with
the perceived hype and misrepresentation of IIT, its claims, and the results of
the <a href="https://www.biorxiv.org/content/10.1101/2023.06.23.546249v1.full">COGITATE</a> study, which apparently came to a head and prompted this drastic
action. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I’m not working in this field and don’t
have a dog in this fight. I don’t know whether publishing such a letter was
warranted or will turn out to be helpful or damaging to the field. I will say
it’s not a good look. But then neither is the hype or the indulgence of
theories that are not actually scientific. My own feeling is that it’s not so
easy to say what is and what isn’t scientific. When it comes to IIT, I think
some aspects of it are specific enough to be testable (or at least people think
they are), while some lead to metaphysical positions I personally find absurd,
such as <a href="http://www.wiringthebrain.com/2018/02/panpsychism-not-even-wrong-or-is-it.html">panpsychism</a>, which are not testable and not, in fact, scientific, in
the operational sense (nor are they intended to be). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Anyway, all of that is preamble. What I
really want to say here is that we do not have any “theories of consciousness”.
We have a bunch of different theories relating to different <i style="mso-bidi-font-style: normal;">aspects of consciousness</i> (very specific
aspects, in some cases). From the outside, it seems to me that many of the
supposed disagreements in the field arise because these theories are really
talking about different things. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For those keeping track, these include the
aforementioned IIT, the Global Neuronal Workspace Theory, Higher-Order Thought
theories, the Attention Schema Theory, Drive Theory, Unlimited Associative
Learning Theory, Beast Machine Theory, and many others (reviewed nicely <a href="https://www.nature.com/articles/s41583-022-00587-4">here</a>).
People in this field do seem to like naming their ideas! </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Even in the very limited domain of visual
perception (which hugely dominates the field), different theories may be
related to different sub-questions. Why does only some sensory information
reach consciousness? How is that information bound together? Where is the
information actually held? Does it all pass to some higher-order areas or are
the details maintained in lower levels? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These kinds of questions have been the
major areas of focus in the field – so much so that they can seem like <i style="mso-bidi-font-style: normal;">what consciousness science is about</i>. (Just
like the field of decision-making often turns out to be just about whether
monkeys can tell if a bunch of dots on a screen are moving more to the right
than the left). But these questions were selected mainly because they can be
operationalized and are experimentally tractable. In my view, the theories that
deal with these paradigms are just not <i style="mso-bidi-font-style: normal;">theories
of consciousness</i> more broadly. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A real grand theory of consciousness, will,
in my view, have to take elements from all the current micro-theories. And then
plenty more, if we are to answer the kinds of questions listed below. And, even
if such a theory can’t currently answer all those questions, it should at least
provide an overarching framework (i.e., what a theory really should be), in
which they can be asked in a coherent way, without one question destabilising
what we think we know about the answer to another one. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, here goes – from my conscious brain to
yours – a non-exhaustive list of questions that occur to me that a theory of consciousness
should be able to encompass:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What kinds of things are sentient? What
kinds of things is it like something to be? What is the basis of subjective
experience and what kinds of things have it? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Does being sentient necessarily involve
conscious awareness? Does awareness (of anything) necessarily entail
self-awareness? What is required for “the lights to be on”? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What distinguishes conscious from <b style="mso-bidi-font-weight: normal;">non-conscious</b> entities? (That is, why
do some entities have the <i style="mso-bidi-font-style: normal;">capacity</i>
for consciousness while other kinds of things do not?) Are there entities with
different degrees or kinds of consciousness or a sharp boundary?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For things that have the capacity for
consciousness, what distinguishes the <i style="mso-bidi-font-style: normal;">state</i>
of consciousness from being <b style="mso-bidi-font-weight: normal;">unconscious</b>?
Is there a simple on/off switch? How is this related to arousal, attention,
awareness of one’s surroundings (or general responsiveness)? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What determines what we are conscious of at
any moment? Why do some neural or cognitive operations go on consciously and
other <b style="mso-bidi-font-weight: normal;">subconsciously</b>? Why/how are
some kinds of information permitted access to our conscious awareness while
most is excluded? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What distinguishes things that we are
currently consciously aware of, from things that we <i style="mso-bidi-font-style: normal;">could be</i> consciously aware of if we turned our attention to them,
from things that we could not be consciously aware of (that nevertheless play
crucial roles in our cognition)?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Which systems are required to support
conscious perception? Where is the relevant information represented? Is it all
pushed into a common space or does a central system just point to more
distributed representations where the details are held? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Why does consciousness feel unitary? How
are our various informational streams bound together? Why do things feel like
*our* experiences or *our* thoughts? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Where does our sense of selfhood come from?
How is our conscious self related to other aspects of selfhood? How is this <i style="mso-bidi-font-style: normal;">sense of self</i> related to actually <i style="mso-bidi-font-style: normal;">being a self</i>?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Why do some kinds of neural activity feel
like something? Why do different kinds of signals feel different from each
other? Why do they feel specifically like what they feel like? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">How do we become conscious of our own internal
states? How much of our subjective experience arises from homeostatic control
signals that necessarily have valence? If such signals entail feelings, how do
we know what those feelings are about?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">How does the aboutness of conscious states
(or subconscious states) arise? How does the system know what such states refer
to? (When the states are all the system has access to).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What is the point of conscious subjective
experience? Or of a high level common space for conscious deliberation? Or of
reflective capacities for metacognition? What adaptive value do these
capacities have?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">How does mentality arise at all? When do
information processing and computation or just the flow of states through a
dynamical system become elements of cognition and why are only some elements of
cognition part of conscious experience?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">How does conscious activity influence
behavior? Does a capacity for conscious cognitive control equal “free will”?
How is mental causation even supposed to work? How can the meaning of mental
states constrain the activities of neural circuits? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If we had a theory that could accommodate
all those elements and provide some coherent framework in which they could be related
to each other – not for providing all the answers but just for asking sensible
questions – well, <i style="mso-bidi-font-style: normal;">that</i> would be a
theory of consciousness. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-329412222701747142023-05-22T08:12:00.001-07:002023-05-22T08:12:29.350-07:00Reflections on “Systems – the Science of Everything”<span lang="EN-GB">Did you ever get the feeling, when you’re
working on some problem (scientific or otherwise), that there are some basic
principles at play that elude you, but that must have been worked out already
by somebody? That’s certainly been my experience in my career in biology,
whether it was in developmental biology, human genetics, neuroscience or other
areas. I’ve felt the joy of discovering new components of systems and working
out some interactions and pathways, but also a nagging feeling that I was not
seeing the whole picture – that I was elucidating details of what was
happening, but not grasping <i style="mso-bidi-font-style: normal;">what the
system was doing</i>. I often felt like I lacked the principled framework to
even approach that question. This was not because such frameworks don’t exist
but because I had never learned about them – systems principles had simply not
been part of my education. </span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This seems to be true across many
disciplines. We’re all so specialised that we have to concentrate on the
specifics of our own topics, whether it’s computer science, economics,
biochemistry, cognitive science, or anything else. Discipline-specific
knowledge is key, of course, but across all these areas there are also
higher-order, abstract systems principles at play that we can recognise and
think about and teach about. We can attempt at least a science of everything –
a principled, rigorous, formalisable way to approach complex systems, whether
they are ecologies or economies, neural networks or social networks, organisms
or organisations. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That is what my colleagues and I set out to
do with a new module that we recently taught for the first time at Trinity
College Dublin. It is called (a bit presumptuously) “Systems – the Science of
Everything”. This is one of a diverse set of modules known as Trinity
Electives, which are open to students from disciplines across the university,
taken in their second or third years. My co-coordinators for the module were
Prof. Harun Siljak from the School of Engineering and Prof. Mary Lee Rhodes
from the Trinity Business School. Here’s what we said in our blurb about this
module:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">“Humanity faces a growing number of ‘wicked
problems’, from pandemics, to climate change, to threats to democracy. It is
clear that the solutions to these problems will not come from any one
discipline, acting in isolation. Yet our educational and research systems are
still aligned into traditional disciplinary silos, defined by distinct methods,
jargon, perspectives, and conceptual frameworks. However, across diverse
disciplines, there are often common principles at play, which can be
highlighted by a focus on systems. From organisms to corporations, ecologies to
economies, neural networks to social networks, there are shared dynamics, abstract
mechanisms, and emergent functions that arise through the organisation of
elements, whether those elements are cells, transistors, people, or
corporations. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The aim of this module is to explore those
principles, to recognise commonalities and deep correspondences between
seemingly diverse phenomena, to introduce students to the meta-science of
systems, and to promote interdisciplinary or even supradisciplinary thinking.
Ideas will be presented conceptually, with examples of convergence across
diverse areas, including: genetics, neuroscience, computer science, business,
economics, engineering, ecology, biochemistry, physics, evolution, medicine,
climatology, and sociology.” </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The challenge was to develop a course that
surveyed the many different theories that collectively make up “systems
science” – network theory, information theory, dynamical systems theory, and so
on – but at a level that was accessible to mid-career students from diverse
disciplines. In particular, we could not assume any real level of mathematical
or programming expertise. Our goal was not to make students expert in any of
these areas but rather to expose them to these mostly unfamiliar ways of
thinking and send them back to their own disciplines with a fresh perspective
and an arsenal of new, powerful concepts. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That’s certainly how I’ve felt over my own
career whenever I’ve learned these kinds of ideas – I felt like it made me smarter.
Like I didn’t have to try and work out complicated stuff from first principles
every time I encountered some new topic. Instead, I could often recognise the
dynamics at play and make sense of what was going on (or at least <i style="mso-bidi-font-style: normal;">what kind of thing was going on</i>) with
reference to these general principles.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
curriculum</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We faced a big problem in developing this
curriculum – not in deciding what to include, but in accepting all the things
that we couldn’t include! The course was organised in two, two-hour sessions
per week for eleven weeks of the semester. Our Tuesday sessions were devoted to
lectures and our Thursday sessions to tutorials and group work, using a
software system for agent-based modelling called <a href="https://ccl.northwestern.edu/netlogo/">NetLogo</a> – more on that below.
That meant we had only two hours to cover each topic we chose, and we wanted to
do it from the diverse perspectives of the module coordinators – engineered
systems, living systems, and social systems. In addition, we had brief guest
contributions by colleagues from other disciplines across the university for
many of these topics.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, we couldn’t go deep – all we could
really do was introduce the various ideas, show students that theories about
these topics exist, and hope to engage them in deploying these ideas in the
context of a group project and an individual reflective essay (more on those
below too). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There is no right way to structure this
kind of course, but what we tried to do was introduce the simplest ideas first
and build from there. This is the curriculum we landed on:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Introduction and overview</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">History and philosophy of systems
thinking</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System structures</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System functions</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System dynamics</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Information and Meaning</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Self-organisation</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Evolution and Learning</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Decision-making</span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l5 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">System failures</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Here’s an outline of what each of those sessions
touched on:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Systems intro and overview</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l9 level2 lfo3; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Systems challenges – need for
systems solutions</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l9 level2 lfo3; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">What is a system?</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l9 level2 lfo3; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Idea of common, abstract
underlying principles – why a science of organisation is possible</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l9 level2 lfo3; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Personal reflections of module
coordinators</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">History and key concepts</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l6 level2 lfo12; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB"><a href="https://www.art-sciencefactory.com/complexity-map_feb09.html">Overview and timeline</a> of systems
approaches/theories </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l6 level2 lfo12; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Historical examples: General
systems theory; Cybernetics/control theory; Systems thinking </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l6 level2 lfo12; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Why these approaches fizzled
out (or did they?)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l6 level2 lfo12; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Guest lecture: Philosophy of
systems – entities, boundaries, levels, reduction/holism/emergence, causation</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System structures</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">We can scientifically characterise
the structures of systems</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Boundaries</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Components and connections</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Networks (basics of network
theory)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Hierarchies (scalar (nested); functional)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Markets</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l7 level2 lfo4; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Guest lecture: networks and
hierarchies in an international peace-keeping mission</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System functions</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l3 level2 lfo5; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">The way components are
connected can impart functionality </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l3 level2 lfo5; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Communication channels;
operators</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l3 level2 lfo5; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Basic motifs / primitives
(amplifier, filter, oscillator, switch…)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l3 level2 lfo5; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Logical operations
(informational causation from configuration)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l3 level2 lfo5; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Higher-order functionality by
combining primitives</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">System dynamics</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Global dynamics emerge from
structure and function</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">State space, energy landscapes</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Phase transitions</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Attractors, equilibria</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Chaos and criticality,
non-linearity</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Stocks, flows, variables</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l10 level2 lfo6; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Simulation and visualisation </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Information and meaning</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Organisation can have causal
power</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Shannon information and entropy</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Signal transmission; codes</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Noise and uncertainty</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Mutual information,
correlation, aboutness</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Functional information:
semantics</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Information flow through
networks</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l4 level2 lfo7; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Guest lecture: curiosity-driven
learning in infants</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Self-organisation</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Global dynamics, structure,
behavior from local rules</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Cellular automata</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Synchrony; whole-part dynamics</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Autocatalytic sets</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Protein folding; tissue
morphogenesis</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Embryonic development; gene
regulatory networks; energy landscapes; attractor states</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Selection for persistence and
robustness</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l8 level2 lfo8; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Complex responsive processes
and structuration</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Evolution and Learning</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Adaptation over different timescales</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Basic algorithm of variation
plus selection</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Natural and sexual selection</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Functional design through trial
and error</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Cumulative, directional change,
creativity – the adjacent possible</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Convergent evolution in design
space; discovery versus invention</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Emergence of purpose and
normativity (value, meaning)</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Modularity, robustness and
evolvability</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo9; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Guest lecture: reinforcement
learning in neural networks</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Decision-making</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Optimisation problems</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Bounded rationality</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Speed/accuracy/cost trade-offs;
opportunity costs</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Constraint satisfaction over
multiple goals</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Cooperation and competition</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Metacognition, uncertainty</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Creativity – search space,
escaping local minima</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Behavioral control, policy-setting</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Ethical frameworks for guiding
decision-making </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l1 level2 lfo10; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Guest lecture: Game theory</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l11 level1 lfo2; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">Systems failure</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Unanticipated consequences</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Failure modes and effects
analysis</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Cascading failures</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Catastrophe theory, tipping
points, resonance </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Robustness and fragility</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Fail-safes, redundancy,
degeneracy</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Designing for failure; formal
methods and invariants</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Unintended consequences</span></p>
<p class="MsoListParagraphCxSpLast" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l2 level2 lfo11; text-indent: -.25in;"><span lang="EN-GB" style="font-family: Symbol; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Neuropsychiatric disorders as
maladaptive attractor states</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That is, admittedly, a lot. Each one of
those topics could be a lecture course in itself. All we could hope to do here
is expose the students to these ideas, make them aware that these ways of
thinking exist, and hope that they can see how to incorporate some of the ideas
into their own ways of thinking. Complex systems are complex, but not
hopelessly so. We can use these abstract principles and formalised theories to “grok”
them – to see what’s going on and understand why, even when the details and
particulars vary. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Student
engagement, group work, and assessments</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This module was not designed with a
traditional content delivery focus. Our goal was not to tell students a bunch
of information and then ask them to tell it back to us in an exam. Instead, we
wanted to engage students in thinking about the concepts and principles of
systems and give them opportunities to deploy those concepts in new scenarios,
including through computer simulations. There were three elements of such work:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB">Discussion boards:</span></i></b><span lang="EN-GB">
students were encouraged to engage with online discussion boards, where they
were expected to respond briefly to a prompt and then respond to two other
student contributions. This worked pretty well – most of the students were very
engaged with lots of interesting back and forth. This was also a useful forum
for the coordinators to see if the ideas were landing as we hoped.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB">Group projects:</span></i></b><span lang="EN-GB"> Our
Thursday sessions were devoted to group work, with tutorials on the agent-based
modelling platform <a href="https://ccl.northwestern.edu/netlogo/">NetLogo</a>. These were taken directly from the excellent book: <a href="https://santafeinstitute.github.io/ABMA/" target="_blank">Agent-Based Modeling for Archaeology</a>, by Romnowska, Wren, and Crabtree. <br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Given the varied background of students,
our aim here was not to make them expert NetLogo programmers. Instead, we
wanted to introduce them to the idea of simulation as a powerful approach to
understanding complex systems, while recognising the limits and simplifying
assumptions of any modelling.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Our cohort of sixty students was split into
ten groups of six. At the start of the course, each group selected a project
topic framed around a real-world systems problem. These ranged from strategies
to foster the resurgence of red squirrels in Ireland, to tackling the spread of
misinformation online, to planning the perfect pub crawl in Dublin. The
assignment was to research the topic, identify systems principles at play,
consider which parameters might be modelled and outcomes measured, and
construct a toy model in NetLogo to simulate some of these dynamics. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Most of the students warmed to this
challenge over the eleven weeks of the semester. Each group was quite varied in
background, which meant it took a little while for them to figure out how to
work together effectively, but that was part of the point of the exercise. It
forced students to think about a problem fairly widely at first, but then
narrow it down and formalise it in a precise enough way to be able to model
some aspects of it in NetLogo. This would come naturally to students in some
disciplines, but for others it will have been a new experience. Ultimately, all
the groups presented very credible, some excellent, projects, reflecting a lot
of work and real engagement.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;"><span lang="EN-GB">Individual reflective essay:</span></i></b><span lang="EN-GB"> The final exercise for the students was to submit an essay
reflecting on what they had learned in the course, and considering how systems
principles apply to some topic in their own discipline or to some global
challenge. These ran the gamut from climate change to supply chain management
to the life cycle of stars to Bayesian game theory in Pokémon! There was a
range of performance, of course, but overall the essays showed that the
students really were approaching things with a fresh perspective. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Student
feedback</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Reflections on the group project and in the
individual essays showed that most students really were getting what we hoped
for from this module (some more than others, of course). But before we get too
self-congratulatory, we should recognise it wasn’t all rosy! In module
feedback, some students commented on the workload for a module of this size, the
challenges of learning a new computing language, the difficulty in following shifting
perspectives from different lecturers, unfamiliar jargon, issues with group
dynamics, and some other issues. Some of this is to be expected, but we will
definitely have to look at the workload and also the way we’re presenting
various topics in our next run of this module. We live and learn!</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{margin-bottom:0in;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-75091213877259912732022-12-14T08:55:00.003-08:002022-12-14T09:02:04.320-08:00How many neurons does it take to change a lightbulb? <p class="MsoNormal"><span lang="EN-GB">I’ve been reading this excellent paper
by David Barack and John Krakauer, on “<a href="https://www.nature.com/articles/s41583-021-00448-6">Two Views on the </a><a href="https://www.nature.com/articles/s41583-021-00448-6">Cognitive</a><a href="https://www.nature.com/articles/s41583-021-00448-6"> Brain</a>”, and it made me
wonder about which mode of nervous system function might have come first. To
use their terminology, the “Sherringtonian” view (named after Charles Scott
<a href="https://en.wikipedia.org/wiki/Charles_Scott_Sherrington">Sherrington</a>) focuses on individual neurons as the elementary units of control, computation,
and cognition. In this view, neurons can be thought of as individual relays in
a control circuit (such as a reflex) or as elements performing discrete
logical operations, which can be combined into larger circuits to carry out
more complex computations. It’s all very bottom-up, algorithmic, and
mechanistic (and, indeed, provided the inspiration for artificial neuronal
networks, as conceived by <a href="https://link.springer.com/article/10.1007/BF02478259">McCulloch and Pitts</a>). The “Hopfieldian” view (after John
<a href=" https://en.wikipedia.org/wiki/John_Hopfield">Hopfield</a>), by contrast, takes the view that more global and dynamic patterns of
activity across populations of neurons are the elements encoding and
representing cognitive objects. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The Sherringtonian view can be applied to
simple reflex circuits and seems like the right way to describe what they are
doing and how they work. (It’s certainly the traditional way). By contrast, the
Hopfieldian view seems much better suited to describing the functions of larger
brain regions, especially in the cerebral cortex (see figures below, from the paper). In the Hopfieldian view, the details
of the firings of individual neurons are not so important – what matters are
the global patterns that emerge. Barack and Krakauer propose that those kinds
of dynamical population-based patterns are essential as representational
vehicles for a truly cognitive internal economy of the kind we see in humans. It’s
easy enough to reconcile these two views as different perspectives that apply
more or less in different parts of the nervous system (meaning the human
nervous system). </span></p>
<p class="MsoNormal"><span lang="EN-GB"><br /></span></p><p class="MsoNormal"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTx5OkQYtRdTo3V_8peC1IosB0uUtWyJeVmPEZk3GnXBzVD_sc8PEEb-EZkFm7NtwZttmxTXnDbRJiG7Ypr1Dq-CpKL-MKRLO9ozBJIHEfKXjzLunOBlKB5J8H12pujaHpAl-j4kMifybPlqYDnU3tq-6KTAaVP5hJRCi12TDWGbk1Fw2xRQKTwQSmmw/s1514/Screen%20Shot%202022-12-14%20at%204.43.17%20PM.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1514" data-original-width="1314" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTx5OkQYtRdTo3V_8peC1IosB0uUtWyJeVmPEZk3GnXBzVD_sc8PEEb-EZkFm7NtwZttmxTXnDbRJiG7Ypr1Dq-CpKL-MKRLO9ozBJIHEfKXjzLunOBlKB5J8H12pujaHpAl-j4kMifybPlqYDnU3tq-6KTAaVP5hJRCi12TDWGbk1Fw2xRQKTwQSmmw/w348-h400/Screen%20Shot%202022-12-14%20at%204.43.17%20PM.png" width="348" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbE-LLM9W7rpCG1wPuSL-5aFJTOkhl41X-APsIzdsg-2xwJYNDWXHWqn3bVxZ6s-jmiqcHloIbehxftTFCUIRn3gZXiCbuiDWGp9Qr2KVg0hKjlDB7lYRy7NALhdaZ1rf-79RxIGyqdlFGjBR8dc6V78V_J0n8K4ce2XynfLSjGhMBEtVLYmFTG9mOdA/s1334/Screen%20Shot%202022-12-14%20at%204.43.25%20PM.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1148" data-original-width="1334" height="344" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbE-LLM9W7rpCG1wPuSL-5aFJTOkhl41X-APsIzdsg-2xwJYNDWXHWqn3bVxZ6s-jmiqcHloIbehxftTFCUIRn3gZXiCbuiDWGp9Qr2KVg0hKjlDB7lYRy7NALhdaZ1rf-79RxIGyqdlFGjBR8dc6V78V_J0n8K4ce2XynfLSjGhMBEtVLYmFTG9mOdA/w400-h344/Screen%20Shot%202022-12-14%20at%204.43.25%20PM.png" width="400" /></a></div><span lang="EN-GB"><br /></span><p></p>
<p class="MsoNormal"><span lang="EN-GB">But a different question occurred to me in
thinking about these two modes of function: which one arose first in evolution?
In creatures with very simple nervous systems, do the neurons work in little
Sherringtonian circuits, or did neurons in fact arise as distributed
Hopfieldian networks? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It seems pretty natural, naively, to assume
that population-level encoding and representation would only have evolved once
nervous systems reached a certain size and complexity. That is, that nature
would have started with isolated neural circuits and scaled up from there, by
multiplying and combining them, resulting in some emergent properties that it
then capitalised on. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And maybe that’s right. Maybe creatures
with small nervous systems carry out all their information processing and other
neural functions based on the activities of single neurons and the discrete
transformations carried out by connections between them. And maybe the
functions of each of those single neurons became functions <i style="mso-bidi-font-style: normal;">of</i> <i style="mso-bidi-font-style: normal;">populations of neurons</i>
as nervous systems got bigger. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But maybe it’s completely wrong. Maybe even
the simplest nervous systems actually work in Hopfieldian ways, characterised
by field dynamics, with attractors and low-dimensional manifolds in collective state
spaces, rather than like motherboards composed of discrete logic gates arranged
in particular ways. This raises the question: how many neurons do you need to
create those kinds of collective state spaces? In creatures with really simple
nervous systems, do they even have enough individual elements to generate these
kinds of dynamics? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That set me to wondering: what animals have
the fewest neurons? A <a href="https://twitter.com/WiringTheBrain/status/1589204661156077568">twitter query</a> threw up lots of interesting examples.
The well-studied nematode, Caenorhabditis elegans, was a popular candidate,
with exactly 302 neurons in hermaphrodites (all identified, named, with
developmental lineages and neuronal connections known). But all kinds of other
wonderful creatures were mentioned too, several courtesy of evolutionary
neuroscientist <a href="https://biosciences.exeter.ac.uk/staff/profile/index.php?web_id=Gaspar_Jekely">Gáspár Jékely</a>, who knows all the weirdest and wonderfullest
critters. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These include the dwarf male of the annelid
polychaete species </span><i><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Dinophilus gyrociliatus</span></i><span lang="EN-GB" style="mso-bidi-font-style: italic; mso-fareast-font-family: "Times New Roman";">,
which has 68 neural cells, notably <a href="https://onlinelibrary.wiley.com/doi/10.1002/cne.902720403">concentrated in two centers</a>: its “brain” (or
frontal ganglia) and its penis. This organisation apparently</span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"> “accords well
with the bipartite behavioral pattern, which is entirely devoted to locomotion
and copulation”. Ah, the simple life!</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Even simpler are the parasitic “<a href="https://en.wikipedia.org/wiki/Orthonectida">orthonectid</a>”
annelids<i style="mso-bidi-font-style: normal;">, </i>which grow and divide
inside various marine host species, generating male and female larvae, which
are basically just motile reproductive organs. Some species, such as <i style="mso-bidi-font-style: normal;">Rhopalura litoralis, </i>have a <a href=" https://link.springer.com/article/10.1007/s13127-021-00519-7 ">dozen neurons or so</a>, but the winners are the males of <i style="mso-bidi-font-style: normal;">Intoshia vaiabili</i>, which have precisely two neurons!</span></p><p><span lang="EN-GB"></span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiCJJh4lSjqXYXK6pfH-XZqulUB6lkiWnd_U_I_pa23WVnk70E4f-OkEzhLG2WqAgo6InTr6RZG5mXSs91I06hZNZOyXZvDnFsuXiCe5gzbYqNnWdtkrilexTBksQAnCFxdzbcAYWCtjIOu_i65v3fwaajq9Y2M5Z_qB_mV2fhklG4LFZyKcQTLwbmKTg/s1366/Screen%20Shot%202022-12-14%20at%209.44.37%20AM.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="586" data-original-width="1366" height="171" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiCJJh4lSjqXYXK6pfH-XZqulUB6lkiWnd_U_I_pa23WVnk70E4f-OkEzhLG2WqAgo6InTr6RZG5mXSs91I06hZNZOyXZvDnFsuXiCe5gzbYqNnWdtkrilexTBksQAnCFxdzbcAYWCtjIOu_i65v3fwaajq9Y2M5Z_qB_mV2fhklG4LFZyKcQTLwbmKTg/w400-h171/Screen%20Shot%202022-12-14%20at%209.44.37%20AM.png" width="400" /></a><span lang="EN-GB"> </span></div><p></p><p class="MsoNormal"><span lang="EN-GB">It doesn’t seem possible that a nervous
system with only two neurons could be working by generating dynamical
state spaces. Those neurons have got to be just acting as individual electrical
elements, in a Sherringtonian fashion… right? You can’t have a Hopfield network
with only two neurons! But how many neurons do you need to get those kinds of
population dynamics? And how many did evolution start with? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Naively (I mean, really naively) you might
think, since nervous systems have grown in size and complexity along many
lineages, that they must have started small and simple – with only a few neural
cells. Among extant species, you’ve got sponges, with no neurons, and then
you’ve got things like <a href="https://en.wikipedia.org/wiki/Ctenophora">comb jellies</a> or <a href="https://en.wikipedia.org/wiki/Cnidaria">cnidaria</a>, that have neurons (quite a
few, as it happens). So how many neurons did the first critter with neurons
have?!?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Did evolution start with just a couple
neurons and build from there? That doesn’t seem to have been the case. Examples
of animals we see today with very few neurons, like those mentioned above, may
actually have <i style="mso-bidi-font-style: normal;">reduced</i> their numbers
over evolution – perhaps due to adopting a parasitic lifestyle or due to other
ecological reasons that reduced the need for a complex nervous system (like
their only behavior being copulation!). It seems more likely that evolution
started with lots of <i style="mso-bidi-font-style: normal;">proto-neurons</i>,
which then evolved into lots of neurons.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There are a number of somewhat competing
(maybe really complementary) hypotheses about when and where neurons arose, and
what problems they solved for early multicellular animals. On a cellular level,
most of the components that neurons use to do their jobs were already present
and being used in other types of cells. This includes the machinery for
regulating electrical potential across the membrane (ion channels and
transporters), for coupling electrically to neighboring cells (gap junction
proteins), or for communicating with other cells chemically (secretory systems
and a diverse range of receptors). The real specialisation of neurons may have
been their morphology – their long, branching projections that allow them to
contact cells far away, bypassing intervening cells, and to connect to multiple
cells at a time. In addition, their polarity – having an input side and an
output side – allows them to propagate signals in a directional fashion. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These make them ideal for solving one of
the main problems that arises in multicellular animals – the need to coordinate
movements of all of their parts. Many simple animals have sheets of
myoepithelial cells, which are electrically coupled and capable of contraction.
(Not quite muscles, but muscle-like epithelia). <a href="https://en.wikipedia.org/wiki/Sponge">Sponges</a>, for example, are
capable of rhythmic movements that rely on traveling waves through such sheets.
What neurons give you is a more specific way to coordinate the contractions of
these sheets of cells, which, in parallel, may have evolved into more discrete
contractile units, i.e., <i style="mso-bidi-font-style: normal;">muscles</i>. One
hypothesis for the early evolution of nervous systems – the “<a href="https://journals.sagepub.com/doi/abs/10.1177/1059712312465330">skin-brain thesis</a>”
– posits that neurons emerged as specialised cells intercalated within these
myoepithelia, providing a “horizontal” coordination across the entire animal. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNoiurbq-fl2atigCwUAJFgKojqeWuXyOyY31FLWJtIiHmQAirdPHM7Gs51DhQcOUMN4olwAOawaRJix9AFP40LicSHZ0SwU8RrrspYOPqMBOVBBqVpbqvHCIFbzLesoJKUgrxVOip7ibo0L5jzII70d5YOqhlfvk8VE3VJFSEvKnP4F9oTOQOma-25g/s1094/Screen%20Shot%202022-12-14%20at%204.49.21%20PM.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1094" data-original-width="1014" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNoiurbq-fl2atigCwUAJFgKojqeWuXyOyY31FLWJtIiHmQAirdPHM7Gs51DhQcOUMN4olwAOawaRJix9AFP40LicSHZ0SwU8RrrspYOPqMBOVBBqVpbqvHCIFbzLesoJKUgrxVOip7ibo0L5jzII70d5YOqhlfvk8VE3VJFSEvKnP4F9oTOQOma-25g/w371-h400/Screen%20Shot%202022-12-14%20at%204.49.21%20PM.png" width="371" /></a></div><span lang="EN-GB">An alternate hypothesis focuses on chemical
communication systems. Many simple animals also have secretory systems of
peptides or hormones that can modulate the contraction of these sheets of
cells. The release of such chemical signals is typically not very localised,
however. Again, neurons provide a solution – the ability to target release of
chemical signals at very specific sites in the organism (along with the ability
to selectively control responsiveness through differential expression of
receptor proteins). The “<a href="https://pubmed.ncbi.nlm.nih.gov/33550946/">chemical-brain hypothesis</a>” proposes this kind of
localised chemical signaling as the earliest function of nervous systems. </span><p></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB"></span></p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-d7-rdB6idJVc9_M8ItUOijcSZum4jKIWUJqb2YDCF4J1MYrJWdQP0NQyMcXQQsiVtZC14H_ZDcp37V-A8eLVSPXpXLSUbsDswRz71aXdSLZ2B_UFSSfvuRMYv5o9jvo21BzIr5rwkPmDS2JUlTBfzHseEZpP9D-rkdBYGk103tS4a0HyPcEeHgQdYg/s1158/Screen%20Shot%202022-12-14%20at%204.49.33%20PM.png" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1158" data-original-width="864" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-d7-rdB6idJVc9_M8ItUOijcSZum4jKIWUJqb2YDCF4J1MYrJWdQP0NQyMcXQQsiVtZC14H_ZDcp37V-A8eLVSPXpXLSUbsDswRz71aXdSLZ2B_UFSSfvuRMYv5o9jvo21BzIr5rwkPmDS2JUlTBfzHseEZpP9D-rkdBYGk103tS4a0HyPcEeHgQdYg/w299-h400/Screen%20Shot%202022-12-14%20at%204.49.33%20PM.png" width="299" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">This figure and the one above reproduced from: Arendt, Detlev (2021)<br /><div class="dropBlock__holder js--open" data-db-target-of="cited" data-top-position="true"><div class="citation__meta"><div class="article-data"><span class="author">
</span><a href="http://doi.org/10.1098/rstb.2020.0347"><span class="article-title">Elementary nervous systems</span></a><span class="abbrevTitle"> Phil. Trans. R. Soc. B</span><span class="volume">376</span><span class="articleId">20200347</span><span class="pageRange">20200347</span></div></div></div></td></tr></tbody></table><span lang="EN-GB"><br /></span><p></p>
<p class="MsoNormal"><span lang="EN-GB">There are arguments in favour of both of
these hypotheses and <a href="https://pubmed.ncbi.nlm.nih.gov/33550948/">perhaps both functions emerged</a> in a coordinated fashion. In
both cases, it’s notable that what is posited is a “horizontal” coordinating
function, rather than a “vertical” connecting function that links sensory
inputs to motor outputs in some specific, reflex-like way. Neurons obviously
offer the potential to make such functional couplings between particular
stimuli and coordinated behavioural responses, once they are in place, but that
may have been a secondarily evolving role.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What’s important for our discussion is
this: in both these models, neurons emerged as new elements <i style="mso-bidi-font-style: normal;">in a pre-existing network</i> of
non-neuronal cells. Those cells were already interconnected, often both
electrically and chemically – comprising fields or populations with emergent
dynamics. It’s not that neurons were added to these networks from outside –
it’s more likely that some of those cells <i style="mso-bidi-font-style: normal;">became</i>
neurons. The earliest neurons may thus have been born from and into Hopfieldian
collectives. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Barack and Krakauer specifically propose
population patterns as vehicles representing cognitive objects – elements they
argue are necessary to explain high-level human cognition. (An argument I agree
with). But perhaps the Hopfieldian model is just how neurons work, more
generally. Maybe it’s how multicellular organisms work – as fields of cells,
rather than discrete, machine-like components. Perhaps the Sherringtonian
model, if it applies at all, reflects a derived function, an exception to this
more general pattern. Or maybe it’s just an artefact of a forced perspective –
an illusion of specificity created by an experimentally isolated system. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We teach neuroscience using the reflex
circuit as a tidy, well-behaved, easily understandable exemplar to illustrate
neural circuit function. This is potentially misleading in a number of ways.
First, it emphasises an input-output function and gives an <a href="https://pubmed.ncbi.nlm.nih.gov/33317833/">erroneous view</a> of
the nervous system as a passive, stimulus-response machine.
Second, as <a href="https://brocku.ca/MeadProject/Dewey/Dewey_1896.html">pointed out by John Dewey</a>, focusing on the unidirectional reflex
ignores the crucial return part of the “circuit” – the action of the organism
that changes the nature of the stimulus it’s receiving. And third, starting with the reflex can give the impression that such
circuits are somehow the building blocks of the whole nervous system, or at
least the most primitive instantiation of what can become more complex kinds of
circuits. But there’s no indication that reflex circuits represent a primitive
“kernel” from an evolutionary point of view. <span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It’s striking that the Sherringtonian
approach has not succeeded in revealing the logic of the workings of even
simple nervous systems or isolated subsystems. For example, the full connectome
of the C. elegans nervous system has been known for decades, and all kinds of
powerful tools have been applied to studying how the nervous system mediates
and governs the small repertoire of behaviors that these animals display. And
yet, even the simplest behaviors resist any reduction to a few discrete circuit
elements, as discussed <a href="https://pubmed.ncbi.nlm.nih.gov/23866325/">here</a> by Cori Bargmann and Eve Marder.
The capability to record activity from all the neurons in the animal, during
awake behavior, is likely to change that, but this involves a move to a more global
<a href="https://pubmed.ncbi.nlm.nih.gov/33551783/">dynamical systems perspective</a>, describing trajectories through state space,
rather than discrete logical computations.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The same can be said for the well-studied
lobster stomatogastric ganglion, which is clearly best thought of as a dynamical system with various <a href="https://pubmed.ncbi.nlm.nih.gov/35302489/">possible operating regimes</a>. And there are multiple other examples, from <a href="https://pubmed.ncbi.nlm.nih.gov/32699071/">hydra</a> to leeches
to <a href="https://pubmed.ncbi.nlm.nih.gov/32916090/">fruit flies</a> to <a href="https://pubmed.ncbi.nlm.nih.gov/34880130/">zebrafish</a>, where these kinds of population-based, dynamical
systems approaches are providing crucial insights. (All echoing <a href="https://link.springer.com/book/10.1007/978-1-4471-0371-4">pioneering work by Walter Freeman</a> and much more recent perspectives, such as Luiz Pessoa’s new
book, <a href="https://mitpress.mit.edu/9780262544603/the-entangled-brain/">The Entangled Brain</a>). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In a way, the debate between the
perspectives of Sherrington and Hopfield parallels the <a href="https://pubmed.ncbi.nlm.nih.gov/11624298/">earlier debate</a> between
Santiago Ramon y Cajal and Camillo Golgi about the nature of the nervous
system. Golgi argued that neurons comprise a continuous reticulum, while Cajal
contended that individual neurons were physically separated from one another
and should be considered independent units. Cajal was right, of course, on an
anatomical level – neurons really are discrete cellular units, rather than a cytoplasmically
connected reticulum or syncytium. But perhaps Golgi was closer to the mark,
from a functional sense. Maybe no neuron is an island – maybe, right from the
get-go, evolutionarily speaking, neurons functioned as members of populations,
fields of cells with shared dynamics, collectively traversing common state
spaces. </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-87359534435774214632022-08-17T02:23:00.005-07:002022-08-17T02:23:48.004-07:00Getting to the bottom of reductionism – is it all just physics in the end?<span lang="EN-GB">There was some interesting <a href="https://twitter.com/patrick_baud/status/1557781946423562240">recent discussion</a> on Twitter regarding claims made in a new book by physicist <a href="https://en.wikipedia.org/wiki/Sabine_Hossenfelder">Sabine Hossenfelder</a>, in which she at least seems to assert that everything that
happens in the universe is reducible to, and deducible from, the low-level laws
of physics. Strikingly, she presents this view as an irrefutable scientific
fact, rather than an arguable philosophical position. It’s worth digging into
these ideas to probe the notion that the behavior of all complicated things,
including living organisms, just comes down to physics in the end. </span>
<p class="MsoNormal"><span lang="EN-GB"> </span><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB"><a href="https://twitter.com/patrick_baud">Patrick Baud</a> quoted several passages from the book, “<a href="https://www.penguinrandomhouse.com/books/616868/existential-physics-by-sabine-hossenfelder/">Existential Physics</a>”, that argue that
reductionist theories are the only game in town. With the important caveat that
I have not read the book in full, and granting that some additional nuance is
probably added elsewhere, it is worth quoting these passages in full to try and
get the gist of these arguments. I’ve interspersed a few brief comments between
the quoted sections:<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">“Countless experiments have confirmed for
millennia that things are made of smaller things, and if you know what the
small things do, you can tell what the large things do. There’s not a single
known exception to this rule. There is not even a consistent theory for such an
exception.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This can be taken in several ways. If it
just means that, if, at any given moment, you know what all the bits of a
system are doing, then you know what the complete system is doing, then it’s
trivial. (It is in fact a statement about us, and what we know, not really
about the system, per se). If, however, it’s implying that all the causes of the
behavior of a given system originate in the laws governing the smallest
elements (i.e., bottom-up), then it’s a much bolder claim, one which she seems
to be making here:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">“A lot of people seem to think it is merely
a philosophical stance that the behavior of composite object (for example, you)
is determined by the behavior of its constituents – that is, subatomic
particles. They call it reductionism or <i style="mso-bidi-font-style: normal;">materialism</i>
or, sometimes, <i style="mso-bidi-font-style: normal;">physicalism</i>, as if
giving it a name that ends in <i style="mso-bidi-font-style: normal;">-ism</i>
will somehow make it disappear. But reductionism – according to which the
behavior of an object can be deduced from (“reduced to” as the philosophers
would say) the properties, behavior, and interactions of the object’s
constituents – is not a philosophy. It’s one of the best established facts
about nature.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">First, it’s very much a philosophical
position, and a highly debatable one, as I hope what follows will illustrate. Second,
reductionism should not be equated with materialism or physicalism – there are
non-reductive forms of both those stances. They basically just say: “no magic!”
They don’t say anything about the nature of causation in physical systems and
certainly don’t rule out whole-part or top-down causation. Third, “reduced to”
and “deduced from” are equated here, but in reality are not the same thing.
Reducing something to the behaviour of its parts is an explanation. Deducing a
behaviour from those parts is a prediction, which is often much harder, and
which, in a sense, includes explaining how it came to be, not just it’s behavior
at a given moment. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And finally, the phrase “and interactions of
the object’s constituents” is doing a lot of heavy lifting here – it’s what
governs those interactions that is at issue. You can obviously say that a
system behaves the way it does, at any given moment, because its particles are
arranged in a certain organisation (and the laws of physics then entail its behavior).
But you can just as well say that the particles are arranged that way (i.e., they got
arranged that way) because they create a system that behaves that way. This is
answering a diachronic “how come?” question, rather than a synchronic “how?”
question. These perspectives are complementary, not conflicting. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">Hossenfelder continues: <br /></span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">“We certainly know of many things that we
cannot currently predict, for our mathematical skills and computational tools
are limited. The average human brain, for example, contains about 1000 trillion
trillion atoms. Even with today’s most powerful supercomputers, no one can
calculate just how all these atoms interact to create conscious thought. But we
also have no reason to think it is not possible. For all we currently know if
we had a big enough computer, nothing will prevent us from simulating a brain
item by item.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There’s a revealing assumption here – that
conscious thought is “created by the interaction of atoms”. Is that the right
way to think about it? I mean, atoms are certainly involved – any kind of
physical structure with dynamics which support consciousness must be composed
of atoms. But is that the right level to look for what makes those structures
or those dynamics special? If you start with that position, then you’re making
a circular argument. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">“In contrast, assuming that composite
systems – brains, society, the universe as a whole – display any kind of
behavior that is not derived from the behavior of their constituents is
unnecessary. No evidence calls for it. It is as unnecessary as the hypothesis
of God. Not wrong, but ascientific.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Well, this is throwing down the gauntlet! It
casts any kind of holistic, non-reductive thinking as mystical – on the level
of religious superstition. This will be news to all the chemists, biologists,
psychologists, sociologists and practitioners of all the other “special
sciences”. Physics rules, and that’s that. All the action is really at the
bottom. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It’s not, however, entirely clear what
“derived from” means here. Again, if it just means that a full description of
the behavior of the particles of a system entails a full description of the
behavior of the whole system, well, no one’s going to argue with that. If you
know what all the atoms in my car are doing, you know what the car is doing. If,
however, it is meant to imply that such a description provides an explanation
of why the system is the way it is, how it came to be, or why it behaves that
way, well then I, for one, certainly will argue. Your detailed picture of all
those atoms of my car (and me, as the driver) won’t tell you that I’m driving
to pick up milk.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Just to make clear that Hossenfelder is not
an outlier in these positions, here’s a <a href="https://medium.com/starts-with-a-bang/yes-the-universe-really-is-100-reductionist-in-nature-3d5aa4bd434f">more explicit statement</a> from <a href="https://en.wikipedia.org/wiki/Ethan_Siegel">Ethan Siegel</a>:</span></p>
<p class="MsoNormal"><span lang="EN-GB"><br /></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">“…the
fundamental laws that govern the smallest constituents of matter and energy,
when applied to the Universe over long enough cosmic timescales, can explain
everything that will ever emerge. This means that the formation of literally
everything in our Universe, from atomic nuclei to atoms to simple molecules to
complex molecules to life to intelligence to consciousness and beyond, can all
be understood as something that emerges directly from the fundamental laws
underpinning reality, with no additional laws, forces, or interactions
required.”</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That really makes it quite explicit. Not
only can the laws of physics help us understand why a system behaves the way it
does, they can explain “the formation” of such systems – i.e., how they came to
be the way they are. That may be true for things like atoms and planets and
galaxies, but we’ll see below that it falls short for more complex entities,
including living organisms. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Siegel goes on to say that: “</span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">The alternative
proposition is emergence, which states that qualitatively novel properties are
found in more complex systems that can never, even in principle, be derived or
computed from fundamental laws, principles, and entities.”</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is a common contrast to draw –
reductionism versus emergence. But emergence is a famously slippery and
contentious concept, so much so that Siegel (like Hossenfelder) thinks any such
explanations contravene not just reductionism but physicalism and amount to
appeals to the supernatural or divine. Again like Hossenfelder, he takes them
to be anti-scientific. (For a counter, see this <a href="http://www.wiringthebrain.com/2022/05/the-riddle-of-emergence-where-do-novel.html">discussion on emergence</a>).
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A more apt contrast to draw is between
reductionism and <a href="https://en.wikipedia.org/wiki/Holism">holism</a>. Regrettably, “holism” seems to carry some mystical
connotations for some scientists as well, possibly due to its centrality in
some Eastern religious philosophies and its cachet among New Age woo-merchants.
But, in scientific terms, this is really a contrast between completely
bottom-up causation and the (very much non-supernatural) idea that the
organisation of the whole may entail constraints that collectively govern the
behavior of the constituents. Much more on that below. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Physicist <a href="https://en.wikipedia.org/wiki/Sean_M._Carroll">Sean Carroll</a> has <a href="http://philsci-archive.pitt.edu/19311/">similarly argued</a>
that the forces and equations of the <a href="https://en.wikipedia.org/wiki/Standard_Model">Standard Model</a> (or Core Theory) of quantum
physics are “causally comprehensive” (at least within the ranges of normal
experience – i.e., not near a black hole or the speed of light).
He grants – in what he calls in his book <a href="https://www.amazon.com/Big-Picture-Origins-Meaning-Universe/dp/1101984252">The Big Picture</a> “poetic naturalism” – that it’s convenient to talk about things at other levels, but the
implication is that this is at best a useful fiction. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Anyway, I was going to respond on Twitter
with some thoughts, but they got so long I decided to list them here as a blog
instead (but still in tweetstorm/bullet point format). Some (perhaps many) of
these points are arguable, but I think they make a good case for the importance
of higher-order causation in understanding many aspects of the universe,
including our own existence. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Let’s consider some reductionist claims:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 1: If we know the detailed
microstates of all the particles in a system at a given moment, then we know
all the information about the macrostate of the whole system. This is trivial
and obvious. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">[Though <a href="https://en.wikipedia.org/wiki/Philip_Ball">Philip Ball</a> notes that even this is
not universal! It’s not true of entangled states, in which information about
the whole state is not reducible to information about its component particles.]</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 2: If we know the detailed
microstates of all the particles in a system at a given moment, AND we can
submit them to the equations of the Standard Model, then we can predict what
the next state will be.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is a MUCH stronger claim, and it
appears to be false, given the fundamental indeterminacy at quantum levels. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We can only – in principle, not just in
practice – make a statistical or probabilistic prediction of the possible
subsequent states of the system. We can predict these probabilities very, very
accurately, but in practice, so far, only for systems of very limited scale and
complexity. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But we can’t predict the actual outcome of
any given “run” or observation or measurement – only what the distribution of
many such measurements would be if it were possible to make them and remake
them from the identical starting position.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, the claim that conditions at any given
moment, plus the “laws of physics”, fully determine the state of a system at
the next moment (and arbitrarily far into the future) <a href="http://www.wiringthebrain.com/2020/07/escaping-flatland-when-determinism.html">appears to be false</a>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 3: It could still be claimed that for
any given system, all the important causal interactions happen at the lowest
levels, even if some are random. It’s all physical forces playing out between
particles or quantum fields. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Note that such a view has no historicity –
it doesn’t matter how a system arrived at a certain state; all that matters is
what that state is. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Systems like this have no memory – they
reflect a certain arbitrary path that has been followed but they don’t
accumulate any complexity. <b>They can’t do anything and they’re not for anything</b>.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Assumption: Note how the reductionist
position already assumes that “systems” exist – collections of particles that
have some integrity as an entity and autonomy from the environment, often with
some internal structure.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But how would such systems even come into
existence in a causally reductionist universe, without any historicity? The
equations of the Standard Model, by themselves, can’t explain this tendency. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, once there is some randomness,
which creates a possibility space, <i style="mso-bidi-font-style: normal;">statistical
principles</i> will come into play across collections of particles, over time.
The laws of thermodynamics will favour some arrangements over others. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Some arrangements will be more stable than
others – some will dissipate more free energy than others (or maximise the rate
of entropy maximisation in the universe as a whole, even while local entropy decreases).
Things will tend to get organised.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Now a simple mathematical principle will
apply: <b>more stable arrangements will persist longer</b>. Note that what matters for
stability is the global patterns of matter and forces and the patterns of flux
– i.e., the dynamics of the macrostates, not the particulars of the
microstates.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 4: A reductionist might counter that
any macrostate must supervene on some particular microstate. So it all comes
down to the details at any given moment!</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In fact, this relationship only goes one
way – a given microstate must correspond to a given macrostate. But, for the
purposes of determining thermodynamic stability, a given macrostate may be
<a href="https://en.wikipedia.org/wiki/Multiple_realizability">realised by multiple</a> possible microstates. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That is, the universe itself does
coarse-graining – it’s not just something we do for convenience. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If you want to claim this is all also “just
physics”, well, fine, but it’s not just bottom-up causation derived from
quantum theory. And we’ll see below how it leads to complex chemistry and
ultimately to biology. <span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 5: Another (very strong!)
reductionist claim is that once we know the laws governing the behavior of
subatomic particles, all other theories or principles can be derived from it. This
position admits that higher-order principles exist but claims they are not
fundamental.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This appears to not be the case. For
example, Hamilton’s <a href="https://en.wikipedia.org/wiki/Stationary-action_principle">principle of least action</a> or Jaynes’ principle of <a href="https://en.wikipedia.org/wiki/Principle_of_maximum_entropy">maximum entropy</a> or the <a href="https://en.wikipedia.org/wiki/Free_energy_principle">Free Energy Principle</a> cannot be derived from the Standard Model.
(At least as far as I know!)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There are all kinds of other <a href="http://www.wiringthebrain.com/2022/05/the-riddle-of-emergence-where-do-novel.html">systems principles and dynamics</a> – familiar to engineers, economists, computer
scientists, biochemists, evolutionary biologists – that do not derive from the
laws of physics. They just hold. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The algorithm of natural selection is a
pertinent example – iterations of mutation and selection will allow change to
accumulate, complexity to increase, and functionality or adaptedness to emerge.
This is independent of the physical medium (and, indeed, the algorithm is
applied in all kinds of areas).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Principles like these apply on the global
scale – to the organisation of systems. And they appear to be every bit as
fundamental as the equations of quantum field theory. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Crucially, they do allow for historicity –
in fact, they make it inevitable. Whatever system is favoured at any given
moment becomes the initial conditions for the next moment. Because of fundamental
randomness, this generates an <a href="http://www.wiringthebrain.com/2019/05/were-principles-of-life-invented-or.html">exploratory</a> and potentially “progressive”
dynamic. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If a system happens into one specific state
at time t, this may mean it can now reach a new, even more favoured state at
time t+1. (Stuart Kaufmann’s “<a href="https://www.edge.org/conversation/stuart_a_kauffman-the-adjacent-possible">adjacent possible</a>”)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This dynamic can lead to the amplification
of very small fluctuations. Indeed, such random fluctuations are necessary to
break symmetry (e.g., of the cosmic inflation) and allow inhomogeneities to
emerge (like the formation of galaxies, stars, and planets).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The universe will thus become structured.
Higher-order entities will arise, with a tendency to persist through time.
(This is tautological but not trivial). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This opens the door to higher-order
causation. But what does this mean? If we think of whole-part causation, this
normally means the whole comprises some organisation of the parts, which
collectively constrain each other. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Claim 6: In a sense, this just means
there’s a solution to the global problem of all the force vectors – an energy
minimum or at least transiently stable organisation of the system. A
reductionist could claim this will just emerge bottom-up. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And of course this is true – *given the
organisation at time t*. But in a universe with a real possibility space, some
organisations <i style="mso-bidi-font-style: normal;">will have been</i> more
likely to exist at time t. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So the probability of any given state at
time t+1 depends on the prior probabilities of all the possible states that
could have existed at time t. The path is historical.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Given that the universe is expanding, the
space of possible states is too – faster than the physical stuff can
equilibrate. That is, the maximum <i style="mso-bidi-font-style: normal;">possible</i>
entropy of the universe is increasing all the time, but the <a href="https://www.informationphilosopher.com/solutions/scientists/layzer/">actual entropy lags behind</a>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This means that the absolute amount of
information (i.e., structure or local order) in the universe can increase, even
while the absolute entropy is also increasing, because the possible entropy is
increasing even faster! </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Now we get to another crucial factor,
hinted at above – <a href="https://royalsocietypublishing.org/doi/10.1098/rsfs.2011.0062">feedback or selection, through time</a>. Not instantaneous whole-part
relations, which suggest a kind of circular causation, but diachronic relations
that extend through time – a spiral, not a circle. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Any given configuration that is stable
enough to persist for some time generates a new adjacent possibility space,
which may allow the system to reach an even more stable state, and on and on. Now
we can see the kind of dynamic that leads to the emergence of increasingly
complex dissipative systems. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Here, the structure of the whole system
(“inherited” from time t) creates the initial boundary conditions that shape
the possibility space at time t+1 – a whole-part causation that is not
logically circular due to it being diachronic. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The organisation of the system imposes
constraints on its components. These constraints are <a href="https://mitpress.mit.edu/9780262545662/">every bit as causal</a> as the
physical forces at play – that is, they contribute to governing the way the
system will evolve from moment to moment.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Forces are thus not the only causes. Indeed,
you won’t have any physical forces without some structure, some inhomogeneities
or gradients. As <a href="https://www.qub.ac.uk/schools/SchoolofBiologicalSciences/Connect/AcademicStaff/DrKeithFarnsworth/">Keith Farnsworth</a> argues, using Aristotle’s terms, there are no efficient causes without
formal causes. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In fact, higher-order constraints can
become even more causally important than the lower-level details, due to the
coarse-graining and multiple realisability at play. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This kind of complexification can lead to
the emergence of life. Living systems exist far from equilibrium and perform
work to stay that way. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">They are therefore under selective pressure
to find solutions that afford the greatest dynamic stability. (Very different
from the inert stability evident in a crystal). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Particular patterns of dynamic relations
(e.g., in networks of chemical reactions) can, through all kinds of feedback
loops in the system, remain stable under a range of conditions. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But they tend to be precarious, especially
in an environment that may itself be quite dynamic. A good way to persist is to
“save the settings” that govern the kinetics of all those reactions in a
chemically inert substrate that is itself held apart from all that activity. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Then if the system is perturbed, it can
re-equilibrate by reference to that stable informational resource. That is the
primary function that DNA performs. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The benefit of course is that the DNA can
be replicated, the cell can divide, and the structure can be recapitulated in
the daughter cells, again by reference to the genetic informational resource, thus
allowing <i style="mso-bidi-font-style: normal;">reproduction</i>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">DNA can thus act as a store of information
and a substrate for natural selection. If a mutation arises that alters the
system dynamics and makes it more likely to persist in whatever environments it
encounters, then that mutation will be selected for. And negative selection
will conversely act against mutations that impair persistence.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These two kinds of natural selection will
act at the population level with a ratchet-like mechanism, meaning change can
accumulate along various possible directions. Progress can be saved at each
step along the way. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Causation in these systems is now
inherently informational and historical – they are the way they are because of
the history of their ancestors’ interactions with the environments they
encountered.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And the way they are imposes constraints on
the components. They are now aligned towards a purpose – persistence. This kind
of causation is absent from a reductionist’s worldview.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The effects of natural selection can lead
to a new kind of structure: a compartmentalised hierarchy, where different
elements of the system are acting over different time-scales.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Some of these can provide top-down
constraints to simultaneously manage short-term and long-term contingencies in
an optimal manner. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is yet another kind of causation,
distinct from whole-part. It is actually part-part causation, but it relies on
a nested, hierarchical structure, where information flows bottom-up and top-down
and side-to-side, with each part trying to satisfy its own constraints, based
on the context supplied by the rest of the system. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Crucially, those configurations can encode
control policies – what to do in the case of some internal or environmental
conditions. Optimal policies will have been selected for based on prior
experience.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is <i style="mso-bidi-font-style: normal;">doing
things for reasons</i>. There are no reasons in a reductive world, where all
the causation inheres at the lowest levels. But where exploratory dynamics lead
to the emergence of true complexity, in the form of life, reasons become
<a href="https://www.mdpi.com/1099-4300/24/4/472">perfectly real causes</a> of what happens. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Note that none of this requires “new
physics” or in any way contravenes the Standard Model. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The laws describing the low-level forces
remain the same. They are just subject to additional constraints in the form of
initial and boundary conditions – no magic required!</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But the system now crucially has
historicity packed into its configuration – it means there is a why as well as
a how, to how it evolves. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Ultimately, if we want to really understand
things in the universe above the scale of atoms, we need to take seriously the
evidence that such entities and systems behave according to higher-order
principles – the particles are just the stuff they’re made of. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The accusation that these higher-order
principles are somehow unscientific or mystical or appeal to supernatural forces
is thus unwarranted. Indeed, to claim that the successes of particle physics in
its own arena mean that every phenomenon at every scale and degree of
complexity will also ultimately be explainable by these low-level laws is such
an extrapolation beyond empirical evidence that it is the position that starts
to look like an article of faith. :-)<br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"><span style="mso-spacerun: yes;"> </span></span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-55783251749229184992022-07-15T08:57:00.002-07:002022-07-15T08:57:13.180-07:00On conceptual rigor: “What do we take ourselves to be doing?”<span lang="EN-GB">I had the pleasure recently of attending a
Festschrift celebration for Prof. <a href="https://celebratingdorothy.web.ox.ac.uk/home">Dorothy Bishop</a>, who has been a leading light
in the study of neurodevelopmental disorders (especially speech and language
disorders) for decades. She has also been a vocal and effective proponent of
improving reproducibility in scientific research, writing on her popular <a href="http://deevybee.blogspot.com/">blog</a>,
on <a href="https://twitter.com/deevybee?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor">twitter</a>, in <a href="https://www.nature.com/articles/d41586-019-01307-2">journal articles</a>, and even presenting in the houses of <a href="https://www.ukrn.org/2021/12/07/stc-enquiry/">parliament</a> on
the subject.<span style="mso-spacerun: yes;"> </span></span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Dorothy’s efforts, along with many others
in the <a href="https://en.wikipedia.org/wiki/Open_science">Open Science</a> “movement”, have helped to highlight crucial issues of
methodological and statistical rigor that have led to irreproducibility across
many fields, along with potential solutions and ways that the scientific
community collectively can address these problems. These efforts are aimed at
improving the quality of what we are doing. But there is sometimes a deeper
question to be asked: why are we doing what we are doing? What is the
conceptual basis for the research we’re conducting? Of course, this is often
very well laid out and supported, but not always. There is frequently a need
not just for more methodological and statistical rigor, but more conceptual
rigor too.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Methodological
and statistical problems</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Problems of irreproducibility have arisen
across fields, with social psychology garnering probably the most public
attention. There is really nothing unique about this field, however – these
problems are extremely widespread, as pointed out already in <a href="https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124">2005 by John Ioannidis</a>. They arise due to under-powered studies, small actual effect sizes, poorly
defined hypotheses, exploratory analyses of a high number of variables, excessive
degrees of freedom in analyses including mining through covariates, lack of
correction for multiple tests, and lack of internal replication – effectively
fishing for significance in noisy data. These practices, compounded by
publication bias, are guaranteed to flood the literature with false positives –
spurious findings that do not replicate. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In the study of neurodevelopmental
disorders, these problems have manifested especially in genetics and
neuroimaging. The issues with <a href="https://en.wikipedia.org/wiki/Candidate_gene">candidate gene</a> association analyses are, by now,
well known. The premise here is that if some trait or condition is heritable,
then there must be some underlying genetic variation associated with it. Some
of that variation may be in the form of common genetic variants in the
population. You may have a hypothesis about what causes a certain condition – say,
derived from knowledge of the relevant pharmacology – and that may lead you to
select a number of “candidate genes” for genetic analysis (such as the
serotonin transporter gene for anxiety or depression, or dopamine receptor
genes for schizophrenia). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The next step is to identify some common
genetic variants in your set of candidate genes and perform an “association
analysis” – this amounts to assessing the frequency of the different versions
in a set of cases and controls and looking for significant differences. If you
find a significant increase of a particular variant in cases, you can infer
that it is associated with increased risk of the condition (in the same way you
would for any epidemiological “exposure”).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The problem was that people searched in
samples that were too small, analysing too many variants at the same time,
without correcting their thresholds for statistical significance for all those
tests, sometimes added in covariates like sex or environmental exposures
(increasing the number of tests multiplicatively), performed inferential
statistics on exploratory data, typically didn’t include an independent
replication sample, and almost exclusively only published “positive” findings.
The result? A decade’s worth of work that generated a literature of false
positives, and a <a href="https://slatestarcodex.com/2019/05/07/5-httlpr-a-pointed-review/">secondary literature</a> aiming to work out the mechanisms
underlying signals that were not real in the first place. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Thankfully, these problems were recognised
by the human genetics community (including journals and funders), prompting a
seismic shift in how genetics is carried out. The only solution was to
cooperate, and very large consortia were formed to allow collection of samples from
tens of thousands of people (rather than tens or hundreds). Technology was
developed to assay common genetic variants across the entire genome, all in the
same genome-wide association study (<a href="https://en.wikipedia.org/wiki/Genome-wide_association_study">GWAS</a>). Computational and statistical
methods were also developed to ensure a high level of rigor: strict correction
for multiple tests, with a genome-wide significance level of 5 x 10-8, control
of possible confounds as much as possible (such as population stratification or
batch effects from different sites), along with independent replication
samples. Importantly, results for all variants are published, whether the individual
association signals reach genome-wide significance or not. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The genetics community thus took the
underlying problems seriously and acted to change the culture and practice of
the whole field. The result has been a <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501872/">decade of discovery</a> of thousands of
common variants statistically robustly associated with all kinds of traits and
disorders. (Whether you think such discoveries are actionable is another
question – more on that below). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Neuroimaging is currently <a href="http://www.wiringthebrain.com/2022/03/go-big-or-stay-home-small-neuroimaging.html">facing up to</a> the
same problems. A <a href="https://www.nature.com/articles/s41586-022-04492-9">recent study</a> by Scott Marek and colleagues shows that so-called
brain-wide association studies (or BWAS, where thousands of neuroimaging
parameters are compared across groups of cases and controls, looking for some
kind of difference somewhere) require the same kind of methodological rigor as
GWAS. That means much bigger samples than are currently used – in the
thousands, rather than the tens. Again, this will require a cultural change in
how this research is carried out – the cottage industry approach just won’t
produce reliable results. (Indeed, the literature claiming to have found all
kinds of imaging “biomarkers” of all kinds of psychiatric conditions is as
inconsistent and irreproducible as the candidate gene association literature).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Meanwhile, some other topics of relevance
to neurodevelopmental disorders seem to have not yet gotten the memo on
reproducibility. This includes a lot of the work on supposed <a href="http://www.wiringthebrain.com/2018/07/calibrating-scientific-skepticism-wider.html">transgenerational epigenetic</a> effects of stress or trauma, for example, or claims of casual effects
of various components of the <a href="https://theconversation.com/gut-bacteria-dont-cause-autism-autistic-kids-microbiome-differences-are-due-to-picky-eating-170366">gut microbiome</a>. The methods used in these fields suffer
from all the same problems outlined above, which are guaranteed to produce more
noise than signal.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The general solutions are pretty clear:
bigger samples, fewer degrees of freedom in the analyses, proper corrections
for multiple testing, independent samples for replication of exploratory
findings before publication, and publishing both positive and negative results.
All of those can be supported by the use of <a href="https://www.cos.io/initiatives/registered-reports">Registered Reports</a>, where a
research design is submitted to a journal and peer-reviewed (with an
opportunity to improve the design at that stage), and where, if the design is
approved, the journal agrees to publish the paper describing it regardless of
how the results turn out. This provides a much more robust way of doing open
and reproducible science, that aims to undercut the perverse incentives that
can lead to systemic biases, especially publication bias. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Conceptual
clarity</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The recognition of these problems and the
changes that various fields are implementing to solve them are very welcome.
They’re crucial in fact, and should be a core part of the training of all
scientists, as well as the upskilling of those of us who were trained before
these issues came to light. But I wonder sometimes if they’re enough to ensure
the science we do is not just reproducible but actually productive. What we
should surely be aiming for is a truly progressive and collective deepening of
our understanding of complex issues. To achieve that, we may need more
conceptual clarity and, frankly, effort, than is sometimes demonstrated. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Philosophers have a phrase they often
employ, when talking or writing about their work – kind of a self-narration of
the processes of thought. They will often say: “What I take myself to be doing
here is…”. This might be something like: I take myself to be making a claim
about the ontic rather than the epistemic status of something or other (i.e.,
what kind of a thing something is, rather than just what we know about
it).<span style="mso-spacerun: yes;"> </span>I used to find this habit a bit
pretentious, even precious, but the more I encounter it, the more valuable I
think it is. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Really, it’s a discipline of reflection on
the activity one is engaged in. It makes you make explicit the premises and
assumptions on which a line of reasoning is based. The reason to lay this out
there, for all to see, is that you might be wrong – not about your conclusions,
but, more fundamentally, about what it is you think you’re doing. Philosophers
make these declarations precisely so that others can challenge them, but it is,
more fundamentally, a useful exercise in clarifying your own thoughts to
yourself. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I’d like to see more scientists adopt this
habit. It would be hugely useful to lay out the premises and assumptions
underlying any given experiment or piece of research. Not just the proximal
ones that have prompted some specific hypothesis, but the deeper ones that
underpin the approach in general – the ones that often go unstated and
unexamined. </span></p>
<p class="MsoNormal"><span lang="EN-GB"><br />
For example, if we’re proposing to <a href="http://www.wiringthebrain.com/2018/11/life-after-gwas-where-to-next-for.html">carry out a GWAS</a> of some psychiatric condition, what is
it we’re hoping to find? Presumably a list of associated genetic variants, but
why? What use will they be? Will they tell us about the underlying “biology of
the condition”? That phrase may have very different meanings, depending on the
nature of the condition. “The biology” of cancer lies at the level of proteins
controlling cellular differentiation, proliferation, cell cycle control, DNA
repair, and so on. These are tightly linked to the functions of implicated
genes. In contrast, “the biology” of something like autism or schizophrenia
manifests at the level of the highest functions of the human mind – social
cognition, conscious perception, language, organised thought. Finding the genes
that convey some risk for the condition is highly unlikely to immediately
inform on the biology underpinning those cognitive processes and psychological
phenomena. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Instead, those GWAS have pointed in general
at genes involved in neural development, reinforcing the view of the symptoms
as <a href="http://www.wiringthebrain.com/2013/03/the-genetics-of-emergent-phenotypes.html">emergent phenotypes</a>, not directly linked to the functions of the encoded
proteins. Given that is the case, we might ask what we take ourselves to be
doing if we’re proposing carrying out ever-larger GWAS of these conditions with
bigger and bigger samples. I’m not arguing against it, just suggesting that
it’s worth making explicit what is to be gained from such an exercise. The
promised insights into “the biology” of the condition are unlikely to just pop
out of such studies, nor will they directly produce a list of new molecular
therapeutic targets, as often suggested. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">More generally, we can ask: <a href="http://www.wiringthebrain.com/2016/05/genetics-in-psychiatry-hope-or-hype.html">w</a></span><span style="mso-ansi-language: EN-US;"><a href="http://www.wiringthebrain.com/2016/05/genetics-in-psychiatry-hope-or-hype.html">hat kinds of things</a> are our diagnostic
categories? Do we take a category like autism or depression or bipolar disorder
or schizophrenia as monolithic, representing a natural kind, or instead as a
diagnosis of exclusion that may encompass a myriad of etiologies and
pathologies? Our basic conceptions here are crucial in answering the question
of what we take ourselves to be doing when, for example, we put a hundred
people with autism in the MRI scanner and compare them to a hundred
neurotypical people. </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">If, say, we’re looking
for some structural brain differences between these groups (as has often been
done), we should be able to explain why we might expect to find such a thing.
The genetics has clearly shown us that “autism” is an umbrella term that
describes an emergent cluster of symptoms at the psychological and behavioral
levels, linked with extremely diverse genetic etiologies. Should we then expect
some commonalities across patients at the level of brain structure, though they
may have a hundred different genetic causes? Would we propose such an
experiment for a category like “intellectual disability”? </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">Analyses of <a href="http://www.wiringthebrain.com/2018/12/if-genomics-is-answer-whats-question.html">gene expression patterns</a> or epigenetic marks in the (post mortem) brains of subjects with these
conditions are similarly vaguely justified, if at all. What is the underlying
premise that is being tested? That all those diverse genetic etiologies might
converge on a pattern of gene expression that underlies the observed symptoms?
Should we expect the symptoms to have a direct molecular underpinning like
that? Or do they reflect instead emergent activity regimes of the dynamical
neural systems of the brain? </span></p><p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">Alternatively, should
we expect to see a direct signature of the primary genetic disruptions in the
<a href="http://www.wiringthebrain.com/2018/12/if-genomics-is-answer-whats-question.html">gene expression patterns</a> of various parts of the adult brain? Attempts to link
altered gene expression profiles to the genes directly implicated by GWAS seem
to imply this idea, yet this premise is not made explicit or justified in the
relevant publications. And it is not obvious, under that model, why so many
distinct genetic etiologies would then lead to a consistent signature across
patients. </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">You could do these
kinds of projects with all the statistical and methodological rigor that could
possibly be brought to bear and still not learn anything useful, if they are
not founded on clear conceptual premises. </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">The same is true in
many areas of cellular and animal neuroscience. Again in relation to
neurodevelopmental disorders, if we make a <a href="https://pubmed.ncbi.nlm.nih.gov/22078115/">mouse model</a> of a mutation associated
with high risk of autism in humans, is this a model “of autism”? Should we
expect some behavioral similarities between the phenotypes observed in the mouse
and in humans with autism? It’s probably better to think of the mouse as just a
model of the effects of that particular mutation, but effects at what level? On
biochemical pathways, developmental outcomes, function of neural circuits or
systems, emergent behavioral phenotypes? </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">Again, how close a
correspondence should we expect between what we see in a mutant mouse at any of
these levels and what we observe in humans? Given that the effects of even
high-risk mutations can vary hugely across individual humans due to differing
genetic backgrounds and idiosyncratic developmental variation, what should we
expect from a single, arbitrary (but inbred) genetic background in the mouse? None
of this is intended to argue against doing this kind of work in cellular or
animal models – it is merely a call for more conceptual clarity in laying out
what can and can’t be gained from investigations at any given level. </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;">To sum up, the focus
on improving statistical and methodological rigor in these and in all fields is
crucial if we want to make our science robust and reproducible. But, if we don’t
take the time to ask ourselves what we take ourselves to be doing, we’re likely
to end up doing something other than what we think. Poorly conceptualised experiments
can waste just as much time and resources as poorly executed ones. </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-30091387859877004402022-06-06T23:53:00.000-07:002022-06-06T23:53:08.392-07:00The evolution of meaning – from pragmatic couplings to semantic representations. <p class="MsoNormal"><span lang="EN-GB">When living creatures perceive something,
they’re concerned with two questions: <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">What is it?</i></b> and: <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">What
should I do about it</i>?</b> You might think that the machinery for answering those
questions evolved in that order – like you’d have to know what something is
before you can know what to do about it – but it seems likely to have been the
opposite. The actions of the simplest creatures when faced with various stimuli
in the world are mostly coordinated by pragmatic couplings – signals that are <i style="mso-bidi-font-style: normal;">prescriptive</i> rather than <i style="mso-bidi-font-style: normal;">descriptive</i>. But these mechanisms laid
the foundation for the evolution of decoupled internal representations with
true semantic content.</span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For living organisms to go on persisting –
which, let’s face it, is their whole schtick – they have to take in energy and
raw materials (food, oxygen) and use them to keep their internal economy
humming. Many organisms manage this process – known as homeostasis – by staying
put and letting resources come to them. The problem with this strategy is that
sometimes environmental conditions change and resources dry up – this is
especially true if the organism’s own activity (along with its friends) uses up
resources locally. A good strategy under such circumstances is to move, and
many creatures evolved various ways of doing that – swimming, sliding, oozing,
crawling, rowing, wriggling, eventually walking, running, and even flying. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But where to go? And how to know?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Some creatures – like a lot of marine
plankton – simply float about on ocean currents and hope for the best. Others
sense a depletion of food or a build-up of toxic waste products in their
current environment and simply set off in a random direction – anywhere else
being better than here. But most have evolved some kinds of specific sensors to
detect relevant substances or objects in the environment in order to control or
inform the direction of movement. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Some of the best-studied examples of these
systems are in the simplest organisms – such as the chemotaxis responses in
bacteria like E. coli. These rod-shaped bacteria move about by rotating a long
thread-like filament called a flagellum that extends from one end and works a
bit like an outboard motor. It has an unusual mechanism of action, though –
when it rotates in one direction, it recruits a bunch of other filaments on the
surface and forms one big propeller, pushing the bacterium forwards. But when
it rotates in the other direction, all those other filaments interfere with it
and the whole bacterium just revolves on the spot. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Most of the time, E. coli will swim in a
straight line for a bit, then tumble around, and then head off in a new,
apparently random direction. However, when they detect some chemical substance
that is a food source – like glucose, for example – they will spend more time
swimming in a straight line, as long as the signal from the detection of the
food source is increasing. In this way, they travel up the concentration
gradient and arrive at the spot with the maximal amount of resources. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The molecular factors that mediate this behaviour
include receptor proteins that protrude like antennae from the surface of the
bacterium and can bind to the food substances, and internal proteins to process
and transmit the signal, ultimately controlling the direction of rotation of
the flagellum. This system is often described in purely mechanistic terms, as
if the bacterium were a passive, stimulus-response machine. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is deeply mistaken – the bacterium is an
endogenously <a href="https://www.mdpi.com/1099-4300/24/4/472">active agent</a>, constantly monitoring its environment for
information that it accommodates to. In isolation, the system I just described
looks very linear and deterministic – as if its activation will push the
bacterium one way or another. In reality, it works in a much more integrative
and holistic manner. E. coli have receptors for many different kinds of
chemicals and other stimuli, including potentially harmful ones. These must all
be integrated to “compute” the most adaptive direction to travel. And the
signals from any potential food source must be compared over adjacent
time-steps for the bacterium to be able to follow a gradient. In addition, all
of this machinery can be modulated by conditions like temperature and
osmolarity and the overall density of other cells.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, there is a lot of integrative
processing going on even in these apparently simple actions of very simple
creatures – so much that it is sometimes referred to as “<a href="https://www.frontiersin.org/articles/10.3389/fmicb.2015.00264/full">basal cognition</a>”.
However, there are some crucial differences from the kind of activities
typically thought of as cognitive in animals or humans. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The main difference with fancier types of
cognition is in what those signals <i style="mso-bidi-font-style: normal;">mean</i>
to the organism. And here we get into some tricky philosophical waters. We’re
used to talking about <i style="mso-bidi-font-style: normal;">information</i> in
scientific terms – it can be localised and even quantified. Meaning is a
slippier concept. It’s obviously much more qualitative and subjective – more
constructed by the interpreter of a signal than residing somehow in the signal
itself. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Pragmatic
meaning</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We can say that the activation of a protein
receptor molecule conveys information to the interior of the cell – information
<i style="mso-bidi-font-style: normal;">about</i> something out in the world. But
it is also information <i style="mso-bidi-font-style: normal;">for</i> something.
The reason bacteria have these receptors is that it is adaptive for them to be
able to detect these substances out in their environment <i style="mso-bidi-font-style: normal;">and do something about it.</i> In fact, these simple systems are
configured in such a way that the organism just does something without
separately apprehending what the signal is about. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The meaning to the organism is not “there’s
glucose here” or even “there’s food here” and it’s not “there’s a dangerous
chemical here” or even “there’s a threat here”. The meaning of these signals to
the organism is simply “approach!” or “avoid!”. They are <a href="https://www.annualreviews.org/doi/10.1146/annurev.neuro.051508.135409?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub++0pubmed">prescriptive</a>, not
descriptive. Or, if you prefer, they are imperative, not indicative. They’re
not pointing at something or reporting what’s out there – they are simply
demanding action. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, in these simple cases, the organism
doesn’t infer what’s out in the world and <i style="mso-bidi-font-style: normal;">then</i>
decide what to do. Really, there’s no inference going on at all – just an
adaptive response. The meaning of these signals is not (yet) in their semantic
content or aboutness – for living organisms, meaning started with <i style="mso-bidi-font-style: normal;">salience</i>. The information is meaningful <i style="mso-bidi-font-style: normal;">for some entity</i>, <i style="mso-bidi-font-style: normal;">relative to</i> <i style="mso-bidi-font-style: normal;">some goal or
purpose</i>.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For living creatures, that purpose is
staying alive. This is the master function that anchors everything else. It
emerges straightforwardly – inevitably – from the action of natural selection.
Organisms that are better at persisting, persist better. Their structures come
to be configured in ways that are best fitted to surviving and reproducing in
their environments. This isn’t just a passive kind of persistence, either –
organisms have to do thermodynamic work to stay alive, and evolution does
design work to favour ones that do it best. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This adaptation includes the configuration
of the systems that integrate sensory signals and control behaviour. Creatures
that tend to approach food sources and tend to avoid danger will do better than
ones that don’t. These stimuli therefore have value, relative to the goal of
persistence. And they come to have meaning – “approach!” or “avoid!” – wired
right into the biochemical configuration, through the cumulative verdict of
natural selection on the types of behaviours that organisms take in response to
them. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The meaning is thus not just in the “<i style="mso-bidi-font-style: normal;">content</i>” of the signals. The currently
active signals conveyed by receptors for these various stimuli are interpreted
in the <i style="mso-bidi-font-style: normal;">context</i> of stored control
policies that are wired into the system.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That’s all well and good – those kinds of
facilities enable simple creatures to navigate their world adaptively. But they
are limited in scope. This is because all that processing is happening at one
level, within a single, shared space over a common timeframe – everything,
everywhere, all at once. You can do a lot by merging a bunch of different
signals like that but you quickly run out of degrees of freedom. There is just
a limit to how many cogs you can compute with in a single, fully interconnected
system before they get jammed up. The solution to this problem is to introduce
some intervening layers and decouple the systems of perception and action. This
is what nervous systems are good for. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Big
beasts with brains</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">When multicellular life emerged, it faced a
new problem. Animals now had bodies with lots of different bits – bits that all
had to be coordinated for the animal to be able to move in an effective
fashion. Muscles evolved to move the bits and <a href="https://journals.sagepub.com/doi/abs/10.1177/1059712312465330">neurons evolved</a> to help
coordinate them – with each other and also in response to sensory information.
At first, these functions may have been performed by the same cells – ones that
sat in the skin, with an outer sensory part and an inner “muscular” part,
capable of contracting. But at some stage, these jobs were split into sensory
cells and motor cells, and then a new type of cell came along, which sat
between them – neurons.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The advantage of having this intervening
layer of neurons is that they could communicate across a whole field of sensors
and motor actuators to coordinate them. And they could do it <i style="mso-bidi-font-style: normal;">fast</i>. The biochemical signaling and
processing that happens in single cells is powerful and efficient, but it’s
slow and not suited to communication over long distances. Neurons use
electrical signals instead, which are extremely rapid, and they evolved complex
shapes and long projections that could connect elements in different parts of
the organism. Organisms thus evolved new, powerful systems for behavioural
control and a new language for internally representing and processing
information. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As nervous systems got more complex, they
started to add more and more internal layers, between the sensory and motor
systems. It’s important to note that there are still some systems where sensory
signals are rapidly coupled to motor outputs, with a minimum of processing. For
example, many insects and fish (and even some mammals) have a hard-wired escape
response to certain visual stimuli, such as a big shadow passing overhead or
looming towards the animal. It’s pretty obvious how such a coupled sensorimotor
system would remain adaptive – it gives speed and reliability to this crucial
survival response. But the real benefits of complex nervous systems come with
the decoupling of perception from obligate action, which, by contrast, gives
greater flexibility and integrative control.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Adding layers of neurons also increases the
amount of processing that can be done on perceptual information, enabling
organisms to extract higher-order information about what is out in the world.
The earliest-evolving senses were smell and touch – the detection of chemical
or mechanical stimuli directly in contact with the organism. Creatures that
rely solely on these kinds of senses cognitively and behaviourally inhabit the
here and now – they have no access to things that are far away from them,
spatially or temporally, and, as a consequence, have not developed the cognitive
resources to think about them or act with respect to them. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The <a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2009.0083">evolution of vision</a> and hearing changed
that. These are distance senses – they’re designed to detect disturbances in
the medium around an organism, whether that is the electromagnetic spectrum or
the vibrations of air or water. This allows organisms to indirectly <i style="mso-bidi-font-style: normal;">infer</i> the presence of objects – most
importantly other organisms – that are out in the world and that may be the
causes of those disturbances. This is not a simple task, however – organisms
have to solve the “inverse problem” and figure out the most likely causes of
patterns of ambiguous stimuli. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is where those intervening levels of
neurons earn their keep. By integrating inputs from the level below, each new
level extracts higher and higher-order information. In the visual system, for
example, the first levels in the retina are just responding to photons of
light. But the next levels are comparing across inputs, performing contrast
enhancement, and feature extraction, making inferences about edges and
orientations and movements. And as that information is processed in the brain
itself, further inferences are drawn about objects, where they are, what they
are, and how they’re moving, relative to each other and the organism itself. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">All of that information is made available
to the rest of the brain to inform action as appropriate, given whatever else
may be happening in the world, what the current state of the organism is, what
its goals are, and so on. This kind of decoupling from action thus provides a
much more flexible control of behaviour, guided by richer and deeper cognition,
operating over longer timescales. It pays to think about the future when you
can literally see things coming from a mile away. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The patterns of neural activity now
constitute <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">internalised representations</i></b> that are “<a href="https://pubmed.ncbi.nlm.nih.gov/17406918/">detached</a>” from obligate
action. Their job is no longer imperative, but indicative, or declarative. Whereas
in simple organisms, the meaning is pragmatic, in more complex organisms, it
becomes truly semantic. We can think of these systems as being configured as
follows:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">- Simple, pragmatic couplings: If A </span><span lang="EN-GB" style="font-family: Wingdings; mso-ascii-font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-char-type: symbol; mso-hansi-font-family: Cambria; mso-hansi-theme-font: minor-latin; mso-symbol-font-family: Wingdings;"><span style="mso-char-type: symbol; mso-symbol-font-family: Wingdings;">à</span></span><span lang="EN-GB"> do X.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">- Complex, semantic representations: If A </span><span lang="EN-GB" style="font-family: Wingdings; mso-ascii-font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-char-type: symbol; mso-hansi-font-family: Cambria; mso-hansi-theme-font: minor-latin; mso-symbol-font-family: Wingdings;"><span style="mso-char-type: symbol; mso-symbol-font-family: Wingdings;">à</span></span><span lang="EN-GB"> then “A” – as in, tell everybody that: “A”.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That information (that “A” is the case) can
then be used to inform all kinds of further cognitive operations, inferences,
and possible actions. It’s a “see something, say something” sort of scenario. The
contrast between these scenarios is like the difference between a thermostat and
a thermometer. A thermostat detects and in the same process acts on information
about the temperature. A thermometer merely reports it (or represents it, to
anyone that is bothered to look at it). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Our visual system does the same thing – it
reports its inferences about what is out in the world to the rest of the brain
(and to the organism as a whole). But this creates a new problem. Now that
these signals are internalised, how do downstream “users” (either other neurons
or brain regions or the organism itself) know what the signal or pattern is
referring to? How is the semantic content anchored? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">No
naked representations</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The meaning can’t be just <i style="mso-bidi-font-style: normal;">given</i>, by the pattern itself, in
isolation – that’s just some neurons firing. As experimenters, <i style="mso-bidi-font-style: normal;">we</i> may know that a given pattern
correlates with something out in the world (which we can see independently). But
how do other parts of the brain, or the whole organism know that? They can’t
see the thing – they only have access to the pattern of neurons firing. <i style="mso-bidi-font-style: normal;">That pattern can’t entail its own meaning</i>.
That would be like looking up the word “car” in the dictionary and finding the
definition: “car”. It can’t define itself. The meaning of the word “car” is
instead given by other associated words that describe its properties and relations:
“</span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">a
four-wheeled road vehicle that is powered by an engine and is able to carry a
small number of people”. </span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A similar process happens in the brain. The
<a href="https://oxford.universitypressscholarship.com/view/10.1093/oso/9780190905385.001.0001/oso-9780190905385">accumulation of such associations</a> starts in infancy, as babies explore their
world, especially by cross-calibrating between their senses. They learn that
things that look like this, feel like that and taste like that and are hard and
about this heavy and I can pick them up and if I drop them they make this kind
of a sound. All of us gradually build up a web of knowledge of these kinds of
properties and affordances of objects – latent schemas that are activated or at
least accessible when we detect an example of that type of object or even when
we think of it. In this way, percepts are grounded on the basis of stored
concepts. And those concepts can get progressively more abstract, encompassing
hierarchical categories, causal relations, and narrative sequences of events –
all the information that an organism needs, in order to decide what to do in a
given situation. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The semantic content of a given
representation is thus embodied in a <a href="https://www.sciencedirect.com/science/article/pii/S1364661313001228">web of associations</a> – a set of linkages
and pointers to other characteristics or properties, themselves represented in
latent structures across the brain. The representation is thus discrete, but
its meaning is distributed. We saw with pragmatic couplings that the meaning of
currently active signals is given by the context of <i style="mso-bidi-font-style: normal;">stored control policies</i>. With semantic representations, the meaning
of any current pattern of neural activity is given by the context of <i style="mso-bidi-font-style: normal;">stored knowledge</i>. All of this is
calibrated through experience, rigorously selected for salience, and ultimately
still used to inform action, just over many more possibilities and much longer
timescales.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The organism still wants to know <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">what
it should do</i></b>. But now it uses decoupled internal representations (and
stored knowledge) of <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">what is out there</i></b> to inform those
choices. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-60356400590395568692022-05-23T09:14:00.000-07:002022-05-23T09:14:25.016-07:00The riddle of emergence – where do novel things come from?<p class="MsoNormal"><span lang="EN-GB">It’s not true, that there’s nothing new
under the sun. The universe is producing novelty all the time. Galaxies, stars,
and planets, where none existed before. New elements, new molecules – life itself,
with the explosion of new species, and eventually new minds, capable of new
thoughts. New <i style="mso-bidi-font-style: normal;">types of things</i> at new
levels of existence – discrete entities composed of smaller entities, arranged
in specific ways. New systems with new properties and new causal powers,
governed by new principles. So where does all this novelty come from? </span>
</p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The term <a href="https://plato.stanford.edu/entries/properties-emergent/"><i style="mso-bidi-font-style: normal;">emergence</i></a> is often used to refer to the appearance of qualitatively
novel states or processes or properties that arise when things are combined in
certain ways. But as with many metaphysical terms, it means different things to
different people and in different contexts, and it’s not always clear what, if
anything, follows from its use. In particular, it is often not stated whether “emergence”
simply refers to an observed phenomenon in need of explanation, or is supposed
to be an element (or even the entirety of) such an explanation. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If we take life, or example, we can say that
<i style="mso-bidi-font-style: normal;">it emerged</i> in the universe. This is a
straightforward description of what happened – it didn’t used to exist and now
it does. In a slightly different way, to say that, at any moment, life as an
ongoing activity of an individual organism is an <i style="mso-bidi-font-style: normal;">emergent phenomenon</i> also seems uncontroversial – living things are
made of components that are not themselves alive, but a whole organism is. On a
finer scale, it seems equally unproblematic to say that living things have a
suite of <i style="mso-bidi-font-style: normal;">emergent properties</i> that are
qualitatively different from those of their components. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These usages are fairly unproblematic, on
their face at least, but they’re also not particularly enlightening. What is
the term supposed to actually imply about the new properties or about the relationship
between the components and the higher-level system? Is it simply that the
“whole is more than the sum of its parts”? That seems trivial, or worse,
nonsensical. How could it be otherwise? Almost by definition, “wholes” have
properties that derive not just from the isolated properties of their parts but
from the way those parts are organised (not “summed”, whatever that might mean).
That’s what makes something an entity, as opposed to, say, a pile. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Then what else is the term emergent meant
to imply? It hints at complexity, non-linearity, and irreducibility, at hierarchical
relationships, where new levels exhibit novel kinds of behaviour, and may even exert
some kind of macroscopic or whole-part or top-down causation back onto the
whole system. Those properties actually sound objective enough – they’re the
kinds of things that complexity and information theory often deal with and can
even quantify (e.g., <a href="https://pubmed.ncbi.nlm.nih.gov/30684520/">1</a>, <a href="https://royalsocietypublishing.org/doi/abs/10.1098/rsta.2021.0150?af=R">2</a>, <a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008289">3</a>). But is that it? Is emergent a synonym for that kind of complexity?
There seems to be an added element that warrants the usage of the term, one
that hinges on something else entirely: subjective, observer-dependent
properties, like unexpectedness, unpredictability, or even interestingness. It’s
not just that a system has new properties – it’s that they’re surprising, maybe
even impressive. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Strong
and weak emergence</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">David Chalmers has an interesting article
probing the <a href="https://philpapers.org/rec/CHASAW">senses of emergence</a>, especially the supposed distinction between
“strong” and “weak” forms. This hinges mainly on whether the new properties are
thought to be unpredictable in principle (the strong version) or are merely
unexpected or difficult for us to predict in practice (the weak version). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For Chalmers, consciousness provides the
only convincing example of a truly emergent phenomenon, in the strong sense.
Here, something qualitatively completely novel and entirely unpredictable emerges
from systems arranged in a certain way. Subjective experience seems to pop into
existence in a way that is almost magical. It’s not just that it is irreducible
to the workings of the physical brain – it’s that it’s not <i style="mso-bidi-font-style: normal;">deducible</i> <i style="mso-bidi-font-style: normal;">from</i> those
workings. Nothing about the physical details could predict that subjective
experience should arise from them. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I’m not convinced that’s completely right,
though. If you look at the trajectory of evolution of cognitive control
systems, you can see how metacognition and recursive self-reference could quite
naturally and adaptively evolve and be selected for. Indeed, you could make a
strong case that their emergence was in fact predictable. That said, it’s still
not obvious why recursive self-reference has to <i style="mso-bidi-font-style: normal;">feel like something</i>. So, consciousness (really subjective
experience at all) still seems like our best candidate for a truly strongly
emergent phenomenon (though I’d be inclined to put life and agency in that
category too). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Chalmers’ discussion of weak emergence highlights
the importance of the sense of unexpectedness: “</span><i style="mso-bidi-font-style: normal;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">To
capture this, we might suggest that weakly emergent properties are interesting,
non-obvious consequences of low-level properties. This still cannot be the full
story, though. Every high-level physical property is a consequence of low-level
properties, usually in a non-obvious fashion</span></i><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">” …</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">He goes on to suggest that “</span><i style="mso-bidi-font-style: normal;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">weak emergence is the phenomenon wherein</span></i><i style="mso-bidi-font-style: normal;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;"> complex,
interesting high-level function is produced as a result of combining simple
low-level mechanisms in simple ways. I think this is much closer to a good
definition of emergence</span></i><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">.” … [Note a similarity here to the idea of global
dynamics emerging purely from local interactions, with no top-down coordination
or control]. </span>
</p><p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">However: “<i style="mso-bidi-font-style: normal;">This conclusion captures
the feeling that weak emergence is a ‘something for nothing’ phenomenon</i>”… </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="font-family: "Times New Roman"; mso-ansi-language: EN-US;">Finally, he suggests that “<i style="mso-bidi-font-style: normal;">an
appeal to principles of design should get us the rest of the way. We design the
game of Life according to certain simple principles, but complex, interesting
properties leap out and surprise us</i>.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">That “something for nothing” aspect seems
to capture what people really mean when they use the term emergence. But it is
also obviously the most problematic aspect of the notion. Both weak and strong
emergence both suppose that the property that is taken to be emerging really
did not in any sense <i style="mso-bidi-font-style: normal;">exist</i> before the
system in which it is observed came to be arranged in that particular way. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Discovery,
not invention</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I think in many cases this is a mistake.
The instances of supposed emergence that most catch our attention are those
where it’s not just true that some new dynamics arise, but where they <i style="mso-bidi-font-style: normal;">enable some new functionality </i>in the
system. This doesn’t have to mean that those dynamics are invented or created
de novo – in many cases, especially in living systems, <a href="http://www.wiringthebrain.com/2019/05/were-principles-of-life-invented-or.html"><b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">they are discovered</i></b></a>. They
don’t just <i style="mso-bidi-font-style: normal;">emerge from</i> the lower
level organisation. Quite the opposite, in fact – they often reflect <a href="http://www.wiringthebrain.com/2017/09/what-are-laws-of-biology.html">systems principles</a> that simply hold in the abstract and that <i style="mso-bidi-font-style: normal;">constrain</i> the organisation of the lower level components (because
they confer some adaptive functionality that becomes selected for). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Evolution is in the design game. But it
produces functional designs by exploration and selection, not by raw creation
from the void. It’s not just luck that living systems have the functionalities
they do. The principles that enable them exist and can be found by evolution. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">For example, there are certain
configurations of elements and relations that will constitute a filter, an
amplifier, an oscillator, a clock, an evidence accumulator, a coincidence
detector, a logic gate; that will execute gain control, or divisive
normalisation, or stochastic resonance; that will extract principal components,
or drive a low-dimensional manifold, or perform Bayesian inference. Those
motifs are seen in gene regulatory circuits, in biochemical signal transduction
pathways, and in neuronal circuits and systems. And of course they’re seen in
our artificial designs as well. The medium doesn’t matter – the functionality
is abstract. <span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The <a href="http://www.wiringthebrain.com/2017/09/what-are-laws-of-biology.html">principles at play</a> are the subject of
fields like cybernetics and control theory and information theory, as well as
dynamical systems theories that encompass the dynamics observed in living
systems, of self-organisation, attractors, criticality, phase transitions, and
so on. It’s interesting to ask, on a meta level, whether these theories are
built of elements that are <i style="mso-bidi-font-style: normal;">fundamental</i>
– Platonic truths that simply hold true – or are themselves emergent, in the weak
sense that they can be derived from theories about simpler things. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But whether the underlying principles are
ultimately fundamental or not, we can still say that many of the functional
properties we observe as we go from level to level in living systems are not so
new after all. They’re common in fact – shared across many kinds of systems at
many different levels. It’s not a matter of getting “something for nothing” –
it’s a matter of finding something useful and hanging on to it.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In these cases, it’s not obvious that the
term emergence really applies or offers any useful insights. The crucial
difference with, say, the complex and surprising dynamics observed in cellular
automata, is that the configurations and dynamics observed in living things are
<i style="mso-bidi-font-style: normal;">for something</i>. They’re not arbitrary.
They’ve been selected for robust functionality. While they may still be
astonishing, they’re not unpredictable in the same sense. There’s an
understandable logic to why they are the way they are. They’ve been through the
filter of natural selection, which is in the business of making predictions –
predictions that the world will continue to be more or less like it was in the
past, and that functionalities that promoted survival will continue to be
adaptive in the future. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Living organisms are made of many such
subsystems, collectively configured to promote the survival and reproduction of
the organism. And the dynamics we observe at the level of higher systems
(composed of many subsystems) are equally relatable to the same kinds of
abstract functional design principles. Evolution has explored that space of
functionalities at each level and selected the ones that confer adaptive
advantages. There is scope in this process for real novelties to arise, through
new combinations of these functional primitives, but this still comes about
through a process of exploration and selection, rather than naïve emergence.
The novel functions don’t just pop into existence spontaneously or come for
free – evolution has to do some design work to find and retain them. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB"> </span></b></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Emergent
dysfunction</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">To put a little twist in the tail, there is
I think a paradoxical corollary to this way of thinking. While the
functionalities embodied in the configurations of living systems have been
selected for and are thus not arbitrary or unanticipated, patterns of <i style="mso-bidi-font-style: normal;">dysfunction</i> may well be. Natural
selection will favour configurations that work and that confer some selective
advantage. Along some lineages, that can lead to complexification of systems,
notably the nervous system. The new selective advantages that come with
increasingly sophisticated cognition may be strongly selected for, but the
downside is that as systems get more complex, they may develop more ways to
fail. Selection for robustness may not keep pace with selection for new or
improved function. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The result, in our own species, may be a
propensity for a minor proportion of individuals to develop emergent states of
brain function that we recognise as psychopathology. Many psychiatric
conditions are quite highly heritable, and seem to reflect the impact of
genetic variants on the program of brain development. The striking aspect of
many of the emergent pathological states is their qualitative novelty. We might
simply have expected such insults to lead to either general or more specific
decrements of cognitive functions. Instead, we get novel states like psychosis
or mania or obsessive-compulsive disorder – not just less function, but a shift
to a different regime altogether. In my book, such states – ones that are
unanticipated outcomes of insults to complex systems selected for other
functions – really do warrant being called emergent. (In line with the
literature on “<a href="https://www.researchgate.net/publication/308083939_Emergent_Failure_Modes_and_What_to_Do_about_Them">emergent failure modes</a>” in systems engineering). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And in this case, thinking of pathological
states in that way has <a href="http://www.wiringthebrain.com/2013/03/the-genetics-of-emergent-phenotypes.html">important implications</a> for how we think about the (very
indirect and non-specific) relationship between gene functions and psychiatric
symptoms. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-36204093256363892382022-03-16T14:20:00.000-07:002022-03-16T14:20:36.968-07:00Go big or stay home! Small neuroimaging association studies just generate noise.<p class="MsoNormal"><span lang="EN-GB">Figuring out the neural basis of
differences between individuals or groups in all kinds of psychological traits
or psychiatric conditions is a major goal of modern neuroscience. In humans, investigating
this has necessarily relied on non-invasive tools like functional or structural
magnetic resonance imaging (MRI). Many thousands of studies have been published
following a similar design: measure some functional or structural neuroimaging
parameters across the whole brain and compare them across individuals or groups
to look for ones that are statistically associated with variation in some
psychological trait, performance on a cognitive task, or membership of one or
other group. Most of these studies have sample sizes in the tens or at best the
low hundreds. A <a href="https://www.nature.com/articles/s41586-022-04492-9">new study</a> by Scott Marek and colleagues shows convincingly that
those sample sizes are at least one or two orders of magnitude too low to
produce reliable results. </span>
</p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This shouldn’t really be news to anyone
who’s been <a href="https://pubmed.ncbi.nlm.nih.gov/23571845/">paying attention</a> either to the field of <a href="https://pubmed.ncbi.nlm.nih.gov/26158966/">neuroimaging</a> or to wider
developments around the <a href="https://pubmed.ncbi.nlm.nih.gov/33954258/">reproducibility and robustness</a> of scientific research. First,
let me make clear that there are lots of neuroimaging studies that don’t suffer
from this problem. These include, for example, studies investigating brain
activation patterns when people are performing various kinds of tasks. These
don’t need huge samples of people because they use tightly controlled
experimental set-ups and usually run hundreds of trials in each individual. <span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">It is the exploratory studies looking for
brain correlates of individual or group differences in some phenotype that are
susceptible to the problems that come with low statistical power and the
aligned issues of excess <a href="https://pubmed.ncbi.nlm.nih.gov/32483374/">researcher degrees of freedom</a> and publication bias.
The existence of these problems is perfectly evident just from surveying the
published literature. For example, there are many hundreds of papers published
claiming to have found a neuroimaging “biomarker” that is associated with any
one of numerous psychiatric conditions (with depression, schizophrenia, and
autism leading the list). None of these have held up. Similarly, there is no
shortage of reported associations of brain imaging parameters with various
personality traits of one kind or another – again, none of these appears to be
robust or reproducible. The empirical observation therefore is that this literature
is not producing real findings. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The reasons why are now painfully clear. I
say painful because the field of genetics has been through this process
already, more than a decade ago. The problem arises in performing exploratory
studies looking for association with any one of thousands of parameters in
samples of only dozens of individuals. It’s clearly a recipe for finding
associations that are merely statistical blips. If you add in a high degree of
flexibility in the way the data are analysed and filter the results with a
hefty dose of publication bias (which selects for “positive” findings), what
you get is a literature that is hopelessly polluted by spurious results. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This accurately characterises the
literature of “candidate gene association studies”, with hundreds of papers
claiming association between some genetic variants and some phenotype, based on
very small sample sizes. By the mid-2000’s, the field had started to recognise
that these reported associations from small studies were <a href="https://pubmed.ncbi.nlm.nih.gov/22878161/">not robust</a>. Very large
consortia were formed to pool samples, especially of patients with various
genetic conditions, and new technologies emerged that enabled genome-wide
association studies (<a href="https://en.wikipedia.org/wiki/Genome-wide_association_study">GWAS</a>) to be carried out. These were much more rigorously
statistically conducted, correcting for the hundreds of thousands of parameters
being tested, including essential replication samples from the get-go, and
reporting all results, statistically significant and not. GWAS have been
<a href="https://pubmed.ncbi.nlm.nih.gov/28686856/">extremely successful</a> in identifying many thousands of common genetic variants
associated with all kinds of traits and conditions. They also clearly
demonstrated that the previously reported candidate gene associations <a href="https://pubmed.ncbi.nlm.nih.gov/30845820/">were spurious</a>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">By analogy, Marek and colleagues look at
BWAS – brain-wide association studies – which compare thousands of brain
imaging parameters across individuals or groups to look for any that are
associated with a given phenotype. By pooling thousands of samples from
multiple datasets, and running exhaustive simulations of different study
designs, they show convincingly that sample sizes of thousands are needed to
detect realistic effect sizes. In particular, they looked at two kinds of
imaging parameters – one functional: resting-state functional connectivity
(RSFC), and one structural: cortical thickness – and assessed whether these
measures across the brain are associated with general cognitive ability or a general
measure of psychopathology. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The results are sobering. The median effect
size of associations detected (the correlation value, <i style="mso-bidi-font-style: normal;">r</i>) was 0.01. That means that the correlation between the brain
imaging parameter and the phenotype only “explained” 1% of the variance in the
phenotype. They go on to show that: </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">“<i style="mso-bidi-font-style: normal;">The
top 1% largest of all possible brain-wide associations (around 11 million total
associations) reached a |r| value greater than 0.06. … Across all univariate
brain-wide associations, the largest correlation that replicated out-of-sample
was |r| = 0.16</i>.” However, they note that: “<i style="mso-bidi-font-style: normal;">Sociodemographic covariate adjustment resulted in decreased effect
sizes, especially for the strongest associations (top 1% Δr = −0.014)</i>.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, with samples in the thousands, these
studies detected associations with very small effect sizes. The corollary is
that if the real effects are so small, samples in the thousands should be
needed to detect them. This means that previously published associations with
samples in the tens (on average, n=25) are VERY likely to be false positives.
The only “results” that could be statistically distinguished with such small
samples are ones with unrealistically large effect sizes. In fact, they state
that: “<i style="mso-bidi-font-style: normal;">At n = 25, two independent
population subsamples can reach the opposite conclusion about the same
brain–behaviour association, solely owing to sampling variability</i>.”</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The implications are stark (and will sound harsh, but now that we know what we know there's no point pretending it's not true):</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">First, the published literature of such
studies must be treated with a huge degree of suspicion, or ignored altogether.
This won’t be easy. No one is suggesting that all those papers be retracted.
This means they will sit there in the literature and likely will continue to be
cited by the unwary, as candidate gene association studies often still are. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Second, researchers should stop doing these
small studies. Funding agencies should stop funding them. Reviewers should stop
endorsing them. Journal editors should stop agreeing to publish them. This will
be, to put it mildly, an enormous culture shock. It was in genetics and it
required major sociological changes on the part of all stakeholders to move
past the flawed methodologies to perform this research on the scale required to
produce reliable results. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But what will small labs do that don’t have
the resources for such huge studies? What will students do if they can’t run
experiments on practically sized samples that can be recruited over the course
of a PhD? I don’t know but I would suggest something else. There’s really no sound argument (scientific,
sociological, or financial) for continuing with these kinds of studies when the
evidence is so clear that they don’t yield trustworthy findings. They simply
waste everyone’s time and effort and resources and <a href="http://www.wiringthebrain.com/2015/12/on-literature-pollution-and-cottage.html">pollute the literature</a> with
noise. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">One solution is to form the kinds of
consortia seen in genetics and indeed already in operation for brain imaging.
This will no doubt be required to collect samples of sufficient size to
detect these very small associations with brain imaging parameters. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">There is, however, a deeper question that I
think should be asked. Why do we think such associations should exist? For
GWAS, the rationale was extremely clear – the traits and conditions under
investigation had been shown to be partly <a href="https://en.wikipedia.org/wiki/Heritability">heritable</a>. That is, some non-trivial
proportion of the variance in these phenotypes is attributable to genetic
variation across the population. This means that there must exist genetic
variants in the population that affect these phenotypes. GWAS is hunting known
quarry. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The same cannot be said for brain imaging
parameters. We simply don’t know that the kinds of traits that people look for
associations with are indeed associated with differences in brain structure or
function that can be detected at the (really pretty crude) level of MRI.
Clearly, we can’t trust the massive literature of small studies that have
suggested this. But what other evidence is there in support of that hypothesis?
We should expect <i style="mso-bidi-font-style: normal;">something</i> to be
different in the brains of people with autism or schizophrenia or depression
versus people without and similarly there must be some neural differences
between people who are more or less neurotic or intelligent or aggressive. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But should we expect those differences to
manifest <a href="http://www.wiringthebrain.com/2020/08/are-bigger-bits-of-brains-better.html">at the macroscale of neuroimaging</a> – at the level of the size of
different brain regions or the thickness of bits of the cortex or the
structural or functional connectivity between various structures? I mean, maybe
they would, but there doesn’t seem to be a very good reason to expect that, as
opposed to expecting much more distributed and microscale differences. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Any such differences (macro- or microscale)
might also be quite idiosyncratic, given the clinical diversity of diagnostic
categories and high-level nature of psychological constructs. There are many ways
to end up with a diagnosis of autism or schizophrenia and many different
profiles of distinct psychological facets that would manifest as high
extraversion or neuroticism. Add the very high background level of individual
differences in brain imaging parameters to begin with and you have to question
the confidence with which imaging association studies have been pursued. There’s
certainly no “ground truth” of heritability that provides a solid motivation
for these kinds of studies. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Indeed, it is notable that the phenotypes
examined in the study by Marek are extremely non-specific: general cognitive
ability and general psychopathology. If any phenotypes are going to show
consistent associations across thousands of people (non-specifically across the
whole brain), it should be these. [One technical question is whether the
imaging results were adjusted for total brain size, which has a known,
substantial correlation with general cognitive ability]. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But should the success in detecting very
weak and non-specific associations with these very general phenotypes imply
that similarly massive samples could find associations between more specific
kinds of phenotypes and more specific brain regions? That doesn’t seem to
follow, necessarily. Frankly, the premise harkens back to naïve ideas of
<a href="https://en.wikipedia.org/wiki/Phrenology">phrenology</a> – that different brain functions could be reliably associated with
the size of different brain regions (as revealed by bumps in the overlying
skull). I'll put my hand up to say I've been involved in these kinds of studies myself in the past, but my expectations have changed over time. <br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">One final question that it seems should be
answerable by people proposing to do these kinds of BWAS at the scale that
would be required (with the financial resources that would be required): what
would be the point? Say we find that some psychological trait or psychiatric
condition is statistically (really weakly) associated across thousands of
people with a tiny difference in some brain imaging measure, like the thickness
of some little bit of the cortex (or multiple bits). Then what? Would such a
discovery (explaining a tiny fraction of the variance in the phenotype) really
tell us much about the underlying neurobiology or cognitive operations? Would
it even provide an entry point for future work? Maybe it would, but it seems
incumbent on such researchers to explain how any positive (really weak)
associations would be followed up. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The comparison with GWAS may be useful
again in this regard. I have <a href="http://www.wiringthebrain.com/2018/11/life-after-gwas-where-to-next-for.html">questioned the feasibility</a> of following up on
common genetic variants that have almost negligible individual effect sizes in
these studies. But at least there is a discrete and definite genetic difference
there that some people have and others don’t, that can be assessed in
biological assays at various levels (biochemical, cellular, physiological). The
same does not hold for brain imaging differences. These would not even be
“there” in individuals – they’re not something you have or you don’t – only an
upward or downward trend in some continuous parameter across many people. It’s
not obvious (to me at least) what you could do with that information. (But perhaps there are very good options I have not thought of).<br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, if I were reviewing a grant proposing a
BWAS, I would first want to make sure that it had a sample size in the
thousands, well enough powered to detect a small effect size. But I’d also want
to know why such an association should be expected in the first place. And, if
any such association were found, how that information would really advance our
understanding of the neural basis of the psychological functions or conditions
in question. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-24217439776727287272022-03-07T04:58:00.000-08:002022-03-07T04:58:22.964-08:00What have we learned from psychiatric genetics? The view from 2022. <span lang="EN-GB">It has been recognised for millennia that
risk of mental illness (broadly defined) tends to run in families. Modern
science has confirmed that psychiatric disorders of all kinds are highly
heritable – that is, the majority of the variation we see across the population
in who is at risk of developing these conditions is genetic in origin. However,
these conditions are not inherited in a simple “Mendelian” fashion, with
clearly segregating risk, like cystic fibrosis or sickle-cell anemia. Instead,
their inheritance is “complex”, which means that many genetic variants are at
play, along with non-genetic factors. In addition, despite clear familial risks
in general, many individual cases are “sporadic”, with no affected relatives. The
last decade has seen tremendous efforts by many hundreds of scientists across
the globe aimed at identifying the genetic risk factors and better
understanding the etiology of psychiatric conditions. </span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The hope is that elucidating the genetics
of these conditions will reveal the underlying biology and provide a pathway to
develop better diagnostics, new therapeutics, and ultimately a personalised
approach to treatment. Given how much progress has been made in identifying
genetic risk variants, it’s worth taking a moment to see what we’ve learned. In
particular, I want to look at how our general conception of the genetics and
biology of these conditions has changed over the past two decades. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">First,
the view from 2000</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In the early 2000’s, the prevailing view
was that the genetics of conditions like autism or schizophrenia was complex
(though it wasn’t at all obvious in what way). It was known that there were
rare genetic conditions that could result in the symptoms of psychiatric
disorders – like <a href="https://medlineplus.gov/genetics/condition/fragile-x-syndrome/">Fragile X syndrome</a> or <a href="https://medlineplus.gov/rettsyndrome.html">Rett syndrome</a> in the case of autism, or
<a href="https://www.genome.gov/Genetic-Disorders/Velocardiofacial-Syndrome">velocardiofacial syndrome</a> in the case of schizophrenia. However, these were
deemed to be exceptional cases – the main pool of “idiopathic” cases (the ones
with no known genetic or organic cause at the time) were considered by many to reflect
the “real” conditions of autism or schizophrenia. This reflects a history of
using these diagnostic terms only for cases where an organic cause could not be
found (like syphilis, in the case of psychosis, for example). It doesn’t, to my
mind, make a lot of sense to apply that logic to genetic causes, and as we will
see below, the dichotomy between rare, Mendelian conditions that result in
these symptoms, and the supposedly common, idiopathic conditions is a mirage
that has evaporated as our knowledge of high-risk genetic factors has
increased.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">When geneticists wanted to find the
mutations causing a particular disease, their main methods prior to the 2000’s
were cytogenetics and linkage analysis. Cytogenetics involves looking down the
microscope at the actual physical chromosomes of people with an illness. In
rare cases, an illness may be caused by a missing or an extra chromosome (as in
Down syndrome) or by a deletion or duplication of a chunk of a chromosome
(though it has to be pretty big to be visible down the microscope) or by a
translocation (where bits of two chromosomes get swapped with each other, often
disrupting some genes). There was one notable success story from this approach
– the identification of a translocation in a large Scottish kindred that broke
the DNA on chromosome 1 in the middle of a gene that was <a href="https://academic.oup.com/hmg/article/9/9/1415/2356151">named DISC1</a> for “Disrupted
in Schizophrenia-1” (though as it happens some carriers of the translocation
were diagnosed with bipolar disorder or major depression). However, mutations
in this gene are extremely rare, making it at best another rare genetic cause
that could be considered as separate to the much larger pool with complex
inheritance. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Linkage analysis had also been exhaustively
pursued for conditions like schizophrenia, bipolar disorder, and depression in
particular. The typical approach was to try and find families with multiple
individuals with these conditions and use genetic markers to track inheritance
of the different chromosomes to try and find regions that co-segregated with
the disease and thus locate a place on a chromosome where a disease-causing
mutation might be found. Those approaches were unsuccessful (in contrast to
many other types of genetic conditions, like cystic fibrosis or haemophilia or
inherited forms of blindness or deafness). It was very difficult to find large
pedigrees where mental illness cleanly segregated over multiple generations.
Pooling pedigrees to give more power for the statistical analyses didn’t help,
suggesting that different families did not share mutations in the same gene. By
this stage, it was thus already clear that these disorders would not have the
simple kind of genetics observed in other, Mendelian conditions, which had
clearly causal mutations in one or a smallish number of genes.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Enter genome-wide association studies, or
<a href="https://en.wikipedia.org/wiki/Genome-wide_association_study">GWAS</a>. The theoretical idea underlying this approach is that common diseases may
be at least partly caused by <i style="mso-bidi-font-style: normal;">common
genetic variants</i>. This was quite a departure from the typical way of
thinking about genetic disease. The idea is that perhaps multiple risk variants
exist in a population but only cause actual disease when enough of them are
inherited at once. This would explain why mental illnesses run in families, as
some families might carry more of these common variants than others, and it
would also explain why linkage analyses had failed – there was no single causal
variant to be found in any given family. Early models <a href="https://pubmed.ncbi.nlm.nih.gov/3426150/">posited</a> on the order of
10-12 such risk variants in the population for a condition like schizophrenia. The
independent segregation of these variants would generate a normal distribution
of burden across the population, with only those inheriting more than some
threshold actually developing disease. This model allowed the supposed
underlying “liability” to be treated mathematically like a quantitative trait,
like height (even if all we could see was the manifestation of illness or not).
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">GWAS took a while to get up to speed, as
sample sizes in the thousands did not produce many positive findings. This
suggested that there were no common variants that had even a moderate effect on
disease risk or they would have been found. (This actually fits with
<a href="https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/resolving-the-paradox-of-common-harmful-heritable-mental-disorders-which-evolutionary-genetic-models-work-best/E4D354587165B797C87A4B53BDCF6EA4">evolutionary expectations</a> – many psychiatric diseases are associated with
reduced numbers of offspring, meaning any variants increasing risk
significantly should be strongly selected against and thus would not be
expected to become common in the population). It thus became clear that models
with 10-12 risk variants were not realistic – there must be hundreds or
thousands of such variants involved. As GWAS studies got bigger (and then much
bigger) <a href="https://www.nature.com/articles/nature13595">risk variants</a> started to be discovered. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These are sites in the genome where the DNA
letter is variable in the population – sometimes an “A”, sometimes a “T”, for
example. If the frequency of one of these is slightly higher in people with a
condition than without, then we say it is “associated” with increased risk of
the condition. Usually, the increase in risk for any given common variant is
tiny – on the order of 1.05 times the baseline. As more and more of these risk
variants were found, the total amount of risk explained started to grow, though
it remained low in absolute terms (on the order of 3-7% of the genetic variance
in risk). Nevertheless, there was an expectation that eventually the remaining
common variation making up this “polygenic” risk would be found, explaining the
genetic risk for the majority of cases in the idiopathic pool. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In parallel, more rare variants with much
higher risk began to be found. <a href="https://pubmed.ncbi.nlm.nih.gov/17363630/">This began</a> with the identification of so-called
copy number variants (CNVs), which are deletions or duplications of small
chunks of chromosomes. These were too small to be detected by traditional
cytogenetics but they could be revealed by new molecular techniques. Some sites
in the genome are particularly prone to the generation of these deletions and
duplications, meaning they recur with an appreciable frequency in the population.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A couple striking observations were made
<a href="https://pubmed.ncbi.nlm.nih.gov/33752146/">from these studies</a>. First, many such variants arise “de novo” – i.e., in the
generation of sperm or eggs. De novo CNVs tended to be associated with much
higher risk and severity of disease than inherited ones. (Consequently, they
also tend to be almost immediately selected against as people who develop
severe disease tend not to reproduce). And second, the same CNVs showed up in
patients with diverse conditions, including schizophrenia, bipolar disorder,
autism, intellectual disability, and even epilepsy. These rare mutations thus
clearly increased risk for psychiatric and neurological conditions in a
non-specific fashion, with some other factors required to explain what
conditions actually emerged in any individual carriers. Indeed, the same CNVs
are often found (at lower frequency) in clinically unaffected individuals in
the general population.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">CNVs are a class of rare mutations that
happen to be particularly amenable to study because they recur at specific sites
in the genome. But we all also carry many rare mutations that are just changes
to individual letters of the genome that occur at random during copying of the
DNA. These can also result in disease but are much harder to find. However,
improvements in sequencing technologies soon enabled sequencing of the “exomes”
(the bits of the genome coding for proteins) or the whole genomes of many
individuals at an industrial scale. These studies are currently identifying
more and more <a href="https://www.medrxiv.org/content/10.1101/2020.09.18.20192815v1">rare mutations</a> (both de novo and inherited) that confer moderate to
high risk of psychiatric illness. The idiopathic pool is thus shrinking all the
time as more and more individuals are found to carry some high-risk mutation. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, that does not make inheritance in
such cases simple. The risk conferred by these mutations is moderate to high
(anywhere from a 3- to 30-fold increase over baseline) but not enough to
explain all the genomic risk. For example, we know that if one monozygotic
(identical) twin has a condition like schizophrenia that the statistical risk
to the other twin is about 50%. Carrying the same genome as someone with
schizophrenia thus increases risk over baseline frequency (~1%) by over 50-fold
– far more than that associated with any of the individual rare, high-risk
mutations. This suggests that other factors in the genome must be increasing
risk in the individuals who actually end up with disease. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">More recent studies are helping to identify
these risk factors and elucidate the nature of their interactions. Some
patients carry single de novo mutations that confer very high risk and are
probably sufficient to explain the occurrence of disease by themselves. Other
patients carrying mutations conveying lower statistical risk have been found to
be more likely to also carry a “second hit” somewhere else in the genome and/or
to have a higher polygenic burden of common risk variants. This is consistent
with a <a href="https://pubmed.ncbi.nlm.nih.gov/20380786/">unifying model </a>whereby the polygenic risk acts as a <a href="https://www.medrxiv.org/content/10.1101/2021.03.30.21254657v1">genetic background modifier</a> of the effects of rare, high-risk mutations. There is thus no need or
reason to suggest that there are separate pools of patients accounting for
these conditions – some entirely caused by rare mutations and some entirely
caused by polygenic burden. <a href="https://www.biorxiv.org/content/10.1101/009449v1">Both factors</a> are likely at play in most, if not all
patients.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Sex is also an important variable. Males
show significantly higher rates of neurodevelopmental disorders (such as
intellectual disability, autism and schizophrenia) than females, while the
reverse is true for conditions like major depression. Females with the former
conditions tend to have <a href="https://pubmed.ncbi.nlm.nih.gov/24581740/">more severe mutations</a> or a greater genomic burden than
male patients. And, when inherited, such mutations are more likely inherited
from the mother than the father. This is consistent with the idea that females
are better able to buffer the effects of high-risk mutations than males. This
greater genomic robustness may be due to the presence of two X chromosomes
versus only one in males. Males are thus exposed to all genetic variation on
the X, which can generally decrease the robustness of developmental processes
and the ability to buffer mutations anywhere in the genome. This is likely the
reason why males across many mammalian species are <a href="http://www.wiringthebrain.com/2020/11/a-sinister-attractor-why-males-are-more.html">more variable</a> for all kinds
of traits. It is unlikely to be the whole explanation however, as it does not
explain why the male vulnerability is much higher for conditions like autism
and attention-deficit hyperactivity disorder, only slightly higher for
schizophrenia, and lower for depression. There are thus likely more specific
neural factors at play as well, reflecting differences in the organisation of
male and female brains. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">With that summary of the trajectories of
research in the field, we can look at some take-home messages and implications
for understanding the biology of these conditions and how this may inform
treatment or the search for new therapies: </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Diagnostic categories have
overlapping etiology. Both common and rare variants tend to increase risk for
psychiatric illness across many diagnostic categories. This doesn’t mean the
categories are not distinct types of endpoints, but does show they can have
common origins. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">The dichotomy between rare and
common disorders is an illusion – the idiopathic pool is likely composed of
patients with one or several rare, high-risk mutations. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">A substantial fraction of
cases, especially of more severe, earlier-onset conditions, is caused by de
novo mutation (explaining sporadic cases).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Mutations in any of hundreds of
genes can confer significantly increased risk.</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">A balance between mutation and
selection explains the prevalence and persistence of these conditions. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">The distinction between simple
and complex inheritance is really a continuum – even high-risk mutations are
modified by genetic background (as is the case for traditional Mendelian
conditions).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB"><a href="https://www.biorxiv.org/content/10.1101/009449v1">Genetic architecture</a> is thus
both heterogeneous and polygenic, involving both rare mutations in many
different genes and a more diffuse polygenic background.</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Polygenic risk is <a href="https://acamh.onlinelibrary.wiley.com/doi/full/10.1111/jcpp.13501">shared across disorders</a> and may also manifest in various cognitive or personality traits,
such as intelligence or neuroticism.</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Sex is an additional
contributor to risk, probably through general effects on neurodevelopmental
robustness (lower in males) and some more specific effects through unknown neural
mechanisms. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">Overall burden is key, with an <a href="https://pubmed.ncbi.nlm.nih.gov/20832285/">architecture</a> of more high-risk single
mutations at the clinically severe end and more combinatorial interactions at
the less severe end.</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">11.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">Making definitive genetic diagnoses and prognoses will be
challenging, as the clinical presentations associated with any given mutation
can be highly variable. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">12.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">The genes implicated by both rare and common variants are enriched
for brain (especially fetal brain) expression, for expression in neurons (of
many types), and for neurodevelopmental processes (very generally). This is an
important reality check. If genes expressed in spleen or pancreas or skin were
turning up, we would rightly be worried that the associations might be
artifactual. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">13.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">There is, however, no real convergence on specific biochemical
pathways or cellular processes or cell types or brain regions. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">14.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">The relationship between genotypes and phenotypes thus remains
stubbornly obscure. There may, in fact, be <a href="http://www.wiringthebrain.com/2013/03/the-genetics-of-emergent-phenotypes.html">no proximal relationship</a> at all
between the molecular and cellular functions of mutated genes and the symptoms
of the disorders that may emerge. </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">15.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">Divergence of outcomes even in monozygotic twins, who obviously
share all their genomic risk factors, illustrates the fact that what is
inherited is not a disorder, but a more general risk for psychopathology.</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">16.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">Whether that risk manifests as actual disease, and which symptoms
emerge, is probabilistic, reflecting additional non-genetic factors. Given the
lack of evidence for systematic environmental risk factors, this diversity of
outcomes may reflect intrinsic stochastic variation in the trajectories of
brain development. <a href="https://press.princeton.edu/books/paperback/9780691204154/innate">Chance</a> thus plays a substantial role in determining which
outcome from a wide possible range is actually realised by the processes of
development in an individual.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">17.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><span lang="EN-GB">The types of symptom clusters we observe (as opposed to all the
unobserved ways the brain could in theory exhibit pathology) likely reflect
reactive or emergent processes in brain development and regimes of function. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In summary, mutations in any of hundreds of
different genes, involved in all kinds of molecular and cellular processes, and
modified strongly by genetic background, can indirectly and non-specifically lead
to altered trajectories of brain development that sometimes result in atypical
outcomes that can manifest in diverse modes of psychopathology. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is, to say the least, frustrating.
Unlike other conditions, like cancer or autoimmune disorders, identifying psychiatric
risk genes did not directly reveal the underlying biology. This is, in my
opinion, because psychiatric conditions do not reflect proximal molecular
biological disturbances in the way these other cellular-level conditions do. The
symptoms of psychiatric conditions affect the highest functions of perception,
cognition, and behavioural control – those are underpinned by distributed
neural circuits and systems, not the actions of specific molecules. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">We won’t, therefore, be <a href="http://www.wiringthebrain.com/2018/11/life-after-gwas-where-to-next-for.html">jumping straight from GWAS</a> or whole-genome sequencing to “druggable targets” for therapeutic
development. If we want to understand social isolation or hallucinations or
mania, we will need to look to neuroscience, not to molecular genetics for
proximal explanations. This is, however, where genetics can provide vital entry
points for experimental follow-up, especially rare mutations of large effect
that can be modelled in animals or other experimental systems. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But the answers will not lie in studying
any such mutations in isolation – each of these will have some idiosyncratic,
even arbitrary array of biochemical, cellular, developmental, and physiological
effects, some proximal, others indirect, cascading and emergent. In my opinion,
making real progress will require a much longer-term meta-project to understand
trajectories of phenotypic convergence and divergence across many such
mutations. These emerge from properties of the developing brain, which can only
be understood as an evolving dynamical system.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The project of psychiatric genetics has
thus been astoundingly successful, thanks to the dedication of thousands of
researchers across the world and the willing involvement of hundreds of
thousands of patients and their families. But it is clearly only the first step
in what will be a much longer journey to understanding the nature of mental
illness. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{margin-bottom:0in;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-25232886007842060502021-08-09T04:20:00.000-07:002021-08-09T04:20:52.639-07:00Telling good science from bad – a user’s guide to navigating the scientific literature<p class="MsoNormal"><span lang="EN-GB"></span><span lang="EN-GB">“Did you find it convincing?” That’s what
one of my genetics professors used to ask us, a small group of undergraduates
who blinked in response, like rabbits in the headlights. We didn’t know we were
supposed to <i style="mso-bidi-font-style: normal;">evaluate</i> scientific
papers. Who the hell were we to say if these papers – published by proper
grown-up scientists in big-name scientific journals – were convincing or not?
We thought published, peer-reviewed papers contained The Truth. But our
professor (the always inspirational David McConnell at Trinity College Dublin)
wasn’t about to let us off so easily. We learned quickly that it absolutely was
our job, as fledgling scientists, to learn how to evaluate scientific papers.</span>
</p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is not a responsibility that can be
offloaded to peer reviewers and journal editors. It’s not that pre-publication
peer review, when it works as intended, doesn’t perform a useful function. But
those supposed gatekeepers of knowledge are as fallible as the primary
producers of the research itself, as prone to hype and fads and influence, as
steeped in the assumptions of their field, as invested in the shared paradigms
and methods, and every bit as wrapped up in the sociological enterprise that is
the modern reality of science. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Passing pre-publication peer review is,
regrettably, <a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000117 ">no guarantee</a> of quality or scientific rigour. Nor is publication
in high-impact journals, which tend to prize novelty in both methods and
results over incremental advances, which, by definition, are more likely to be
robust. Individual readers of the scientific literature – researchers,
clinicians, policy-makers, journalists, and especially students – should be
empowered to critically evaluate scientific publications. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is especially important now as
preprints become more widely adopted, most recently in biology. The rise of
preprint servers such as <a href="https://www.biorxiv.org/">bioRxiv</a> and <a href="https://www.medrxiv.org/">medRxiv</a> is a very welcome advance, busting
the stranglehold of journals on access to scientific research. But it will
require a change in how readers and members of the field engage with published
research (and yes, posting a preprint is making the research public). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The internet has democratised scientific
publishing and it can and should democratise the peer review process too. The
hive-mind can take the place of a few selected reviewers and editors in judging
what work is robust and reliable. Of course we’re not all technical experts in
every area, but there are some general things to look out for that can help
distinguish solid work from more shaky offerings. Other will have their own
lists, but here is what I take to be markers of quality in scientific papers,
or, conversely, red flags:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
good:</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Based on a solid foundation
of prior work</span></span><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Clearly articulated hypothesis,
with an experimental design appropriate to test it </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Alternatively, presentation of
the work as descriptive or exploratory</span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Right question asked at right
level with right tools</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Experimental controls</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Sufficient statistical power</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Appropriate statistical
analyses</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Converging lines of evidence</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Internal replication</span></span><span lang="EN-GB"></span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Conclusions supported by the
data</span><span lang="EN-GB"></span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">All of which is to say that the papers I
find most convincing build on previous work to generate a testable hypothesis
or identify something worth exploring, design an experiment or an analysis at
the right level to test it, perform the appropriate controls (whether
experimental or statistical), don’t rely on a single method or results from a
single experiment or analysis but draw on multiple, preferably diverse lines of
evidence (which may each have their own limitations or confounds or biases, but
at least they should be different ones), replicate their findings (especially
effects or associations that showed up as ‘significant’ but that were not hypothesised
a priori), and limit their conclusions to what is actually supported by the
data. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In short, I like to get a sense that the
authors went to great lengths <i>to convince themselves</i> of their findings and have
been cautious and thoughtful in their interpretation. Conversely, these are the
characteristics that make me say “nope” (sometimes out loud) and move on to the
next paper:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
bad:</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">No clear rationale or
hypothesis </span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Not founded on solid body of
work </span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Wrong level to address the
question</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Reliance on single method or
analysis</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Statistically underpowered</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Data-dredging: just looking through
many measures for some statistically significant ‘finding’ – any effect or
association in any direction </span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Covariate mining, multiplying
likelihood of spurious ‘findings’ </span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Failure to correct for
multiple tests</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">No replication</span><span lang="EN-GB"></span></span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l1 level1 lfo2; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">High likelihood of
publication bias</span><span lang="EN-GB"></span></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"> </span></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">These are papers where it just doesn’t seem like the authors
have a clear idea of what they’re asking – where the hypotheses are vague or
not well justified – and where the experimental design, though it may generate
data (sometimes lots and lots of data), is not well suited to actually
answering any question, at least not at the level that the authors are
interested in (e.g., looking to <a href="http://www.wiringthebrain.com/2018/12/if-genomics-is-answer-whats-question.html?spref=tw">transcriptomics</a> data to answer a systems
neuroscience question, or <a href="http://www.wiringthebrain.com/2019/07/the-murderous-brain-can-neuroimaging.html">MRI data</a> to address a psychological question).</span></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"> </span></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">There may also be lots of technical experiments that are
just poorly done (because many of them are frankly really hard), but it’s often
difficult for non-experts to evaluate these. This is where reviewers who are
real peers in the same subfield are invaluable. Dodgy stats are much more
general, however, and the biggest red flag is a sample size that is simply too
small to reliably detect the kind of effect the authors are interested in or
are claiming is real. (The idea that if some ‘effect’ was detected with only a
small, under-powered sample, <i style="mso-bidi-font-style: normal;">it</i> <i style="mso-bidi-font-style: normal;">is more likely to</i> <i style="mso-bidi-font-style: normal;">be real,</i> is a fallacy – such findings are far more likely to be
false positives). And there are other well known ‘questionable research
practices’ and biases that any reader can learn to be on the lookout for (see references below). <a href="https://www.sciencemag.org/news/2018/09/more-and-more-scientists-are-preregistering-their-studies-should-you">Pre-registration</a>
– now offered by many journals – is a good protection against these dangers and
a positive mark of reliability. </span></span></p>
<h3><span class="css-901oao"><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">Here
are a few examples that I have examined before: </span></span><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">The Trouble with Epigenetics, <a href="http://www.wiringthebrain.com/2013/01/the-trouble-with-epigenetics-part-2.html?spref=tw">Part 2</a>; The Trouble with Epigenetics, <a href="http://www.wiringthebrain.com/2014/04/the-trouble-with-epigenetics-part-3.html?spref=tw">Part 3</a> – over-fitting the noise;
<a href="http://www.wiringthebrain.com/2018/05/grandmas-trauma-critical-appraisal-of.html?spref=tw">Grandma’s trauma</a> – a critical appraisal of the evidence for transgenerational
epigenetic inheritance in humans.<span class="css-901oao"> They happen to be
drawn from the field of transgenerational epigenetics, but the issues are very
general and recognizable and discussed further here: </span><a href="http://www.wiringthebrain.com/2018/07/calibrating-scientific-skepticism-wider.html">Calibrating scientific skepticism</a>; and here: <a href="http://www.wiringthebrain.com/2015/12/on-literature-pollution-and-cottage.html?spref=tw">On literature pollution and cottage-industry science</a>.<span class="css-901oao"></span></span></h3>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Beyond these issues of experimental design, technical
execution, and proper statistics, there are some sociological factors that tend
to make me more skeptical than I would be otherwise when reading some papers:</span></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"> </span></span></p>
<p class="MsoNormal"><span class="css-901oao"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">The dodgy:</span></b></span></p>
<p class="MsoNormal"><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"> </span></span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Part of currently sexy,
trendy field</span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Appeals to other dodgy papers
as support for general paradigm</span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Hype, spin, excessive claims
of novelty</span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Over-interpretation or extrapolation
beyond what the data support</span></span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Claiming to overturn
mainstream thought </span></span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l2 level1 lfo3; text-indent: -.25in;"><span class="css-901oao"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span></span><span class="css-901oao"><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">Someone selling something (or
the potential for them to)</span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">You would think that extraordinary claims
would require extraordinary evidence. The reality in a lot of scientific
publishing is that such claims can get published with only suggestive evidence
because, if they turn out to be right, the paper will get hugely cited. (And
even if they eventually fizzle or are shown not to replicate, the paper may still
attract lots of attention and citations for some time). And when peer reviewers
in the same field have a <a href="http://www.wiringthebrain.com/2018/07/calibrating-scientific-skepticism-wider.html">shared interest</a> in the general paradigm being a thing
(e.g., transgenerational epigenetics or social priming or the gut microbiome
affecting our psychology), then every additional paper that gets published can
be used as support for their own future publications (or grant applications). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As for selling something, sometimes this is
quite overt and declared as a possible conflict of interest. But other times
the work being presented is part of a long process of development of some
reagent or approach that the authors hope may have clinical or commercial value
in the future. There’s nothing wrong with that, in principle – developing new
therapeutics is what pre-clinical work is all about, after all. And potential
profit is one of the incentives that drives that work. But this incentive can
lead to an exaggeration of claims of efficacy, over-extrapolation beyond the
experimental system used, selective focus on supposedly supporting lines of
evidence, and so on. It may be overly cynical, but in these scenarios, I set
the gain on my skepticometer a little higher. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
not even wrong:</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Finally, there are some papers where the
experimental work and statistical analyses are all fine, but that suffer from
much deeper problems in the underlying paradigm. These are ones where the
conceptual foundation is vague, with unexamined and unjustified assumptions,
poorly framed questions, fundamental category errors, or other theoretical or philosophical
issues that mean the authors are not investigating what they think they’re
investigating. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A common example of interest to me is
papers that say such-and-such (a pattern of functional connectivity between
some brain areas, or a profile of post mortem gene expression, or some other
supposed biomarker) is the case “in autism” or “in schizophrenia” or “in
depression”. These implicitly treat these psychiatric diagnostic categories as
natural kinds, when we know that these labels are diagnoses of exclusion for
conditions that are actually incredibly heterogeneous, both clinically and
etiologically. My heuristic in evaluating these papers is to replace the
offending phrase with “in intellectual disability” (which people don’t make the
same error with) and see if the approach makes any sense at all. </span></p>
<h3><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-hansi-theme-font: minor-latin;">Other examples include expecting complex behaviours (often with crucial societal
and cultural factors at play) to be reducible to: differences in size of
certain brain areas (e.g., <a href="http://www.wiringthebrain.com/2020/08/are-bigger-bits-of-brains-better.html">Are bigger bits of brains better</a>?; </span><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;"><a href="http://www.wiringthebrain.com/2019/07/the-murderous-brain-can-neuroimaging.html">The murderous brain</a> - can
neuroimaging really distinguish murderers?; <a href="http://www.wiringthebrain.com/2017/08/debunking-male-female-brain-mosaic.html?spref=tw">Debunking the male-female brain mosaic</a>); levels of expression of certain genes (<a href="https://theconversation.com/epigenetics-what-impact-does-it-have-on-our-psychology-109516">Epigenetics: what impact does it have on our psychology</a>?; <a href="http://www.wiringthebrain.com/2018/12/if-genomics-is-answer-whats-question.html?spref=tw">If genomics is the answer, what's the question</a>? A
commentary on PsychENCODE); or polygenic scores (<a href="http://www.wiringthebrain.com/2019/12/is-your-future-income-written-in-your.html">Is your future income writtenin your DNA</a>?).</span></h3>
<h3><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">These are examples
from my own fields of research – I’m sure readers will have their own bugbears
that exercise them as much as these ones do me. (A common one in psychology is
assuming that effects seen in brief experiments in highly artificial lab
settings will somehow translate to actual behavior in the real world).</span></h3>
<h3><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">Then there are much
deeper philosophical issues affecting whole fields, for example whether a
<a href="http://www.wiringthebrain.com/2019/09/beyond-reductionism-systems-biology.html">reductionist approach</a> in biology is the right one, whether mechanistic concepts
of cells or computational concepts of brains are appropriate, whether the
multifarious factors contributing to complex processes can in any sense be
disentangled, differences between predicting, controlling, explaining, and
understanding, and so on.</span></h3>
<h3><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">Anyway, that’s my
personal user’s guide to navigating the scientific literature. It may seem
cynical, maybe even arrogant to make these kinds of judgments of other people’s
work (though I should confess to having made and I hope learned from some of
the mistakes listed above myself, both as a researcher and a reviewer). But
life is short and the literature is vast and growing at a relentless pace –
considering the issues listed above lets me winnow what’s worth reading in
detail to a more manageable pile. Beyond that, if we want the general public
and our policy-makers to “trust the science” in making decisions on issues of
global impact, then we have a collective responsibility, in my view, to help
curate the scientific literature. </span></h3>
<h3><span style="font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;"><br /></span></h3>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Useful
reading:</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span lang="EN-GB">Ioannidis (2005). </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"><a href="https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124">Why Most Published Research Findings Are False</a>. </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span lang="EN-GB">Button et al (2013) </span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";"><a href="https://www.nature.com/articles/nrn3475">Power failure</a>: why
small sample size undermines the reliability of neuroscience.
</span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Stuart Ritchie (2021): <a href="https://www.penguin.co.uk/books/111/1117290/science-fictions/9781529110647.html">Science Fictions</a> –
Exposing Fraud, Bias, Negligence, and Hype in Science. 2021. Penguin books. (A
super read and one I recommend for all undergrads starting out in biology,
psychology, and related fields). <br /></span></p>
<h1><span lang="EN-GB" style="color: windowtext; font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-hansi-theme-font: minor-latin;">Dorothy Bishop, <a href="http://neuroanatody.com/2017/11/oxford-reproducibility-lectures-dorothy-bishop/. ">Oxford Reproducibility Lectures</a>.</span></h1>
<h1><span lang="EN-GB" style="color: windowtext; font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;">Dorothy
Bishop (2019), <a href="https://www.nature.com/articles/d41586-019-01307-2">Rein in the four horsemen of irreproducibility</a>. <a href="https://www.nature.com/articles/d41586-019-01307-2"><span style="color: windowtext;"></span></a>
</span></h1>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Björn Brembs (2019) </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"><a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000117">Reliable novelty</a>: New should not trump true. <a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000117"><span style="color: windowtext;"></span></a>
</span><span lang="EN-GB"></span></p>
<h1><span lang="EN-GB" style="color: windowtext; font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-hansi-theme-font: minor-latin;">Kevin Mitchell (2017): </span><span lang="EN-GB" style="color: windowtext; font-family: Cambria; font-size: 12.0pt; font-weight: normal; mso-ascii-theme-font: minor-latin; mso-bidi-font-weight: bold; mso-fareast-font-family: "Times New Roman"; mso-hansi-theme-font: minor-latin;"><a href="https://onlinelibrary.wiley.com/doi/full/10.1111/ejn.13801">Neurogenomics –towards a more rigorous science</a>. <br /></span></h1>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="Default"><span style="color: windowtext; font-family: Cambria; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;">Munafo et al. (2017) .<a href="https://www.nature.com/articles/s41562-016-0021"> A manifesto for reproducible science</a>. <br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Tal Yarkoni (2020) </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "– ı\0027E1˛";"><a href="https://cup.org/3s0IcaC">The generalizability crisis</a>. </span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">
</span><span lang="EN-GB"></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span lang="EN-GB">Makin et al., 2018. </span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785265/">Ten common statistical mistakes</a> to watch out for when</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">writing or reviewing a manuscript. <br /></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{margin-bottom:0in;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-88114626424269710292021-04-28T12:55:00.005-07:002021-04-28T12:55:40.366-07:00Reframing the debate around free will - from the morass of moral responsibility to a grounding in biological agency<span lang="EN-GB">A <a href="https://www.theguardian.com/news/2021/apr/27/the-clockwork-universe-is-free-will-an-illusion ">recent article</a> in the Guardian very nicely summarised “the free will debate”, or at least the more visible
parts of it. The debate is a live one as new findings from neuroscience or even
fundamental physics are supposedly constantly and cumulatively limiting any
scope for free will to possibly exist. The article presents the two most
popular positions among scientists and philosophers: free will skepticism and
compatibilism, which are championed by influential figures like Sam Harris and
Daniel Dennett. The trouble is, they are by no means the only possible options,
and, frankly, neither is convincing or satisfactory, in my view, for many reasons.<span style="mso-spacerun: yes;"> </span></span>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">First, they often start out with
definitions of free will or criteria for what would constitute it that are not
just different from each other, but independently highly arguable. Second, both
take determinism to be true, as a given. Free will skepticism argues that
determinism rules out free will. Compatibilism argues that free will is – as
the name suggests – compatible with determinism. What exactly is meant by
“determinism” is not always clearly spelled out, however – there are in fact
various meanings that are often conflated (see below). Usually the arguments
actually rest on a <i style="mso-bidi-font-style: normal;">reductive</i> view of
causality, as much as a deterministic one.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Moreover, the arguments are usually couched
in terms of their implications for moral responsibility, and so the debate
takes place on ground that is doubly treacherous. Indeed, people like Dennett
argue that determinism is compatible with assigning moral responsibility to people
for their “actions”, even though they actually do not make real choices or have
real freedom in selecting such actions. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Anyway, you can read the article for more
details of the respective arguments. The point I want to make here is that
framing the issue solely in terms of these two positions misconceptualises the
problem, misses whole fields of relevant literature, omits a number of other
viable positions, and leads to endless debate, characterised by the two sides talking past each other. This is illustrated by a recent book – <a href="https://www.amazon.co.uk/Just-Deserts-Debating-Free-Will/dp/150954576X">Just Deserts</a> – by Gregg
Caruso and Dan Dennett, in which they not only fail to reach agreement after a book’s
worth of direct dialogue, they fail to even make clear to each other
or certainly to this reader what it is they disagree on. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As a result, many scientists find these
discussions not worth their time (as I get told repeatedly). Which is a shame - first,
because the issues really are of fundamental importance in considering the
human condition (and deeper questions about the nature of life itself).
But also because they can actually be approached from a much more grounded, scientific
perspective. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, here are some suggestions – a
mini-manifesto in twenty points – for ways to approach these issues that I
think can let us make real progress in constructing a new conceptual framework for understanding agency and free will:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Separate questions of whether free will exists from possible
consequences for systems of moral responsibility.</span></b><span lang="EN-GB"> The
latter issue muddies the waters and leads to motivated reasoning. We shouldn’t
be trying to make convoluted arguments to rescue a “kind of free will worth
wanting” (i.e., one that can justify praise and blame). That is almost a
theological exercise. We should be trying to understand what kind of will we
have and what kind of freedom we have.</span></p>
<p class="MsoListParagraphCxSpMiddle"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Don’t start with the most complex version we know of.</span></b><span lang="EN-GB"> You wouldn’t start trying to understand the principles of
aeronautics by studying the space shuttle. You’d begin with trying to
understand much simpler precursors and scaffolding your understanding by
elaborating on basic concepts. We need to similarly ground the study of free
will in the study of biological agency – how it is that living organisms can do
things at all, how they make decisions and select actions, how they can be
autonomous entities that merit being thought of as causes in their own right.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Define and dissociate the different flavours of determinism and
specify the implications and challenges of each kind.</span></b><span lang="EN-GB"> Too often discussions of the “problem of determinism” for free will
slip between very different meanings: </span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">a.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">I’m wired a certain way, due to
evolution and genetics and development and experience and though I make choices
and do what I want, I don’t <i style="mso-bidi-font-style: normal;">decide what I
want</i>. If I didn’t choose all the prior causes constraining me at any given
moment, then I am not really making free choices. (Note that this kind of
fatalism has actually nothing to do with physical determinism).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">b.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">“Every event has a cause”. So
what? I can be the cause. (Unless the additional claim is made that <i style="mso-bidi-font-style: normal;">the real causes</i> are at the lowest
physical levels; i.e., not just determinism, but reductionism).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">c.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">All that apparent choice is
actually an illusion – it’s all just neural circuitry working away. Mental content
is an epiphenomenon – <i style="mso-bidi-font-style: normal;">you’re </i>not
doing anything. (Really neural reductionism seasoned with a pinch of dualism, but
often presented as determinism).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto; mso-list: l0 level2 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">d.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Even the neural circuit view is
illusory – there’s no real function at that level. It all comes down to physics
– the atoms are gonna do what the atoms are gonna do. This is the real hard
determinism where the future is pre-determined and you are not deciding
anything (because possibilities don’t exist). The counterargument – that the
universe is not in fact deterministic – is often dismissed by saying: well,
then randomness settles the outcome and you’re still not deciding anything.
(Note that this is also really reductionism, not determinism).</span></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-left: 1.0in; mso-add-space: auto;"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Make explicit the key problem of reductionism (thinking all the <i style="mso-bidi-font-style: normal;">real</i> causation happens at the lowest
physical level).</span></b><span lang="EN-GB"> In particular, the deterministic
idea that “every event has a cause” is only a problem for free will if <i style="mso-bidi-font-style: normal;">you </i>cannot be such a cause (or if the
meaning inherent in the patterns of neural activity in your brain cannot be
considered to have causal efficacy). </span></p>
<p class="MsoListParagraphCxSpMiddle"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Consider the nature and sources of indeterminacy and its
implications. </span></b><span lang="EN-GB">There is clearly still disagreement
about what current physical theories imply about the nature of reality,
especially the ontological status and origins of indeterminacy, both at quantum
and classical levels. But the majority of favoured theories (from very diverse
angles) incorporate some indeterminacy in a way that gets resolved through
interaction, marking the present as a boundary when the indefinite becomes
definite. This is enough to override worries of a pre-determined future and to
allow non-reductionist causation to occur.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">6.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Give the “rewinding the tape” thought experiment a rest.</span></b><span lang="EN-GB"> The framing of the question as: “could you have done otherwise?” at
any given instant is conceptually misleading. There is no such thing as an
instant. Decision-making happens over time. The real question is: do you
actually have choices open to you in the present (which is not an instant of
zero duration) and can you choose between them? Asking “could you have done
otherwise?” is looking at that process after it’s been completed, when the
possibilities have already been reduced to a definite outcome. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">7.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Develop a broader framework of causation (to include
organisational/structural/configurational/criterial causation).</span></b><span lang="EN-GB"> The fact that the organisation of a system has causal power in
determining how that system behaves (and how its components behave) is utterly
commonplace, but has been banished from the reductionist worldview. There is a
real science of systems that is not just “a convenient way of talking about”
complex things – it really does capture why they behave as they do, in a way
that even complete low-level descriptions miss. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">8.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Understand how freedom (at one level) relates to constraint (at a
lower level).</span></b><span lang="EN-GB"> Constraint is not a bad word.
Organising the components of a system towards some purpose necessarily involves
restricting the degrees of freedom of those components. This is how
higher-level function emerges – how a coordinated system can do things that
uncoordinated components cannot. It’s why we pay football coaches so much
money. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">9.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Develop concepts of causal insulation, coarse-graining, multiple
realisability, hierarchy, and macroscopic causation.</span></b><span lang="EN-GB"> Living organisms resist the drive towards thermodynamic equilibrium
partly by erecting a barrier between “them” and the outside world. This is not
just a physical and chemical barrier, but a <i style="mso-bidi-font-style: normal;">causal</i>
one. They sense what is out in the world through a veil and respond to that
information (not to a transfer of energy or matter). The same thing happens
between neurons or between whole areas in the brain. Causal insulation allows
meaning to be extracted as information is transferred from one element to the
next and allows that meaning to have causal power. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">10.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Operationalise purpose,
function, meaning, and value as crucial causal elements. </span></b><span lang="EN-GB">These properties do not have to be mysterious or vague – they can be
precisely defined and conceptualised in scientific terms. In creatures with
nervous systems, it is possible to develop a framework to understand how
patterns of neural activity have casual power <i style="mso-bidi-font-style: normal;">by virtue of</i> what they mean. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">11.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Clarify the relationship
between pragmatic and semantic meaning.</span></b><span lang="EN-GB"> An
evolutionary view can chart the transition from direct sensorimotor couplings
to uncoupled communication of signals (representations) to higher levels for
more integrative decision-making. These are not mutually exclusive – the brain
uses both.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">12.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Embrace a process view of
life and self</span></b><span lang="EN-GB">. Avoid the trap of thinking about
“instantaneous” states and substances, as opposed to ongoing processes. Life
and self are defined by continuity of processes over time.</span></p>
<p class="MsoNormal"><span lang="EN-GB"><span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">13.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Emphasise the historicity
of living systems (lineages and individuals).</span></b><span lang="EN-GB">
Organisms literally incorporate information about the regularities of their
environment into their own physical structure and use that to set criteria for
future action. This means causation is spread over space and time. And this
kind of historicity packs causal potential into the structure of the organism,
analogous to potential energy – it takes work to put it in there and it can
later be used to do work.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">14.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Consider the evolution of
the nervous system as the development of more and more sophisticated levels of
control of behaviour.</span></b><span lang="EN-GB"> The idea that the nervous
system is dedicated to information processing and logical computations is a
legacy of early thinking in artificial intelligence. While the nervous system
can do those things, that is not <i style="mso-bidi-font-style: normal;">what it
is for</i>. It is primarily a <i style="mso-bidi-font-style: normal;">control
system</i>, the job of which is to define a repertoire of actions and choose
between them. This control system has been elaborated over evolution to give
greater and greater causal autonomy over longer and longer timeframes.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">15.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Avoid dualistic intuitions
about the self as corresponding only to our conscious minds.</span></b><span lang="EN-GB"> Allow that: (a) our consciousness has a physical basis, and (b)
much of our decision-making is done subconsciously, for very good reasons. Most
of our daily behaviour is controlled by habits, heuristics, and policies that (thankfully)
do not require constant conscious supervision. Deliberation and introspection
are possible, however, and understanding such processes should be grounded in the
science of executive function and metacognition, where goals, beliefs, and
desires become objects of cognition. We can and regularly do inspect our own
reasons.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">16.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Avoid abstract problems of
instantaneous self-causation or top-down causation</span></b><span lang="EN-GB">.
It is not that the organisation of the whole system (the brain or the whole
organism) at any given instant somehow simultaneously both comprises and
influences the arrangement of its parts. A realistic picture of decision-making
and action selection involves interaction between different parts of the nervous
system, extended over time, sidestepping this metaphysical pothole.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">17.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Consider how consciousness
supports or enhances the causal agency embedded in neural systems</span></b><span lang="EN-GB">. What more does it get you? Are thoughts a model of one’s own
cognition? Did a need for social communication of beliefs, goals, and reasons
drive the capacity for cognitive introspection? Does this conscious access to
our own reasons provide an opportunity to choose to reconfigure them?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">18.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Develop an understanding
of long-term willed action as an interplay of present freedom and future
constraint. </span></b><span lang="EN-GB">Control of our behaviour extends
through time. The conscious development of character over our lifetimes, active reconsideration of
habits and heuristics, and adoption of goals or policies shape (inform and
constrain) future action. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">19.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Embed this biological
understanding of human agency in the context of culture and society.</span></b><span lang="EN-GB"> People’s choices are constrained by external factors in all kinds
of ways. Even if we establish that human agency is real, that does not mean it
can be deployed by everyone equally across all situations. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoListParagraph" style="mso-list: l0 level1 lfo1; text-indent: -.25in;"><span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">20.<span style="font: 7.0pt "Times New Roman";"> </span></span></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Only then, in my view,
will we be able to relate this perspective to questions of moral
responsibility.</span></b><span lang="EN-GB"> Our systems of morality are
complex, evolved from biological systems of social cooperation, but socially
constructed in diverse ways across cultures. Whether humans are biologically
capable of free action in a general sense is relevant to questions of morality,
but cannot be considered separately from all the social and cultural factors
that also contribute to our moral systems.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Admittedly, that’s a lot. I’m not
suggesting any one of those tasks will be simple or uncontroversial, either
scientifically or philosophically. But I do think it charts out some actionable
areas where a more productive framework for understanding agency and free will
could be developed. The good news is there are lots of people working on lots
of these elements and tons of new theoretical and empirical findings to inform
this work. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Fleshing out this framework is my job in a
new book I am currently writing: <i><b>“AGENTS – How Life Evolved the Power to
Choose”</b></i>, to be published by Princeton University Press in 2022. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And you can hear more about these ideas in
this <a href="https://www.youtube.com/watch?v=gxpbvE8V0Dg">recent talk</a> I gave (virtually) at the Santa Fe Institute. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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{margin-bottom:0in;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-47177250492967913562021-01-13T11:29:00.003-08:002021-01-13T11:29:48.324-08:00Does quantum indeterminism defeat reductionism? (Response to Coel Hellier)<p><b> <span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM:
I’m grateful to Coel Hellier (<a href="https://twitter.com/coelhellier?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor">@colhellier</a>) for writing a <a href="https://coelsblog.wordpress.com/2021/01/11/does-quantum-indeterminism-defeat-reductionism/">blogpost</a> in response to <a href="http://www.wiringthebrain.com/2020/07/escaping-flatland-when-determinism.html">one I wrote</a>
arguing that if determinism falls, it takes reductionism with it. Rather than
expect people to bounce back and forth between these posts, I have pasted
Coel’s entire blog and intercalated my responses, in bold, below. For clarity, I have color-coded his excerpts from my original blog in blue:</span></b>
</p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">After
writing <a href="https://coelsblog.wordpress.com/2020/12/29/science-does-not-rest-on-metaphysical-assumptions/"><span style="color: blue;">a piece on</span></a> the role of metaphysics in science,
which was a reply to neuroscientist Kevin Mitchell, he pointed me to several of
his articles including <a href="http://www.wiringthebrain.com/2020/07/escaping-flatland-when-determinism.html"><span style="color: blue;">one on</span></a> reductionism and determinism. I found this
interesting since I hadn’t really thought about the interplay of the two
concepts. Mitchell argues that if the world is intrinsically indeterministic
(which I think it is), then that defeats reductionism. We likely agree on much of
the science, and how the world is, but nevertheless I largely disagree with his
article.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Let’s
start by clarifying the concepts. Reductionism asserts that, if we knew
everything about the low-level status of a system (that is, everything about
the component atoms and molecules and their locations), then we would have
enough information to — in principle — completely reproduce the system, such
that a reproduction would exhibit the same high-level behaviour as the original
system. Thus, suppose we had a Star-Trek-style transporter device that knew
only about (but everything about) low-level atoms and molecules and their
positions. We could use it to duplicate a leopard, and the duplicated leopard
would manifest the same high-level behaviour (“stalking an antelope”) as the
original, even though the transporter device knows nothing about high-level
concepts such as “stalking” or “antelope”.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: I would describe this position
simply as physicalism. It just states that if you made an exact physical
duplicate of a living being, you would regenerate not just the low-level
positions of all the atoms and molecules, but the high-level organization and
properties as well. Of course you would – the high-level properties inhere in
that organization. I don’t suppose anyone would dispute that, but there’s
nothing reductionist about this assertion, as CH kind of concedes below:</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"><span style="mso-spacerun: yes;"> </span></span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">As
an aside, philosophers might label the concept I’ve just defined as
“supervenience”, and might regard “reductionism” as a stronger thesis about translations
between the high-level concepts such as “stalking” and the language of physics
at the atomic level. But that type of reductionism generally doesn’t work,
whereas reductionism as I’ve just defined it does seem to be how the world is,
and much of science proceeds by assuming that it holds. While this version of
reductionism does not imply that explanations at different levels can be
translated into each other, it does imply that explanations at different levels
need to be mutually consistent, and ensuring that is one of the most powerful
tools of science.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: This stronger philosophical
version of reductionism is indeed my target – the idea that the observed
high-level properties and behaviors of complex systems (indeed even the
existence of those systems in the first place) can in fact be reduced to <i style="mso-bidi-font-style: normal;">and fully explained by</i> the playing out
of all the low-level interactions between the atoms and molecules. I agree with
CH that this version of reductionism “doesn’t work”! But this is not some kind
of straw man, as implied. It is a view that is espoused by many, especially in
discussions on things like free will, and it is the version of reductionism
that I argue is tightly intertwined with determinism.<span style="mso-spacerun: yes;"> </span></span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"><span style="mso-spacerun: yes;"> </span></span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Our
second concept, determinism, then asserts that if we knew the entire and exact
low-level description of a system at time <i>t</i> then we could — in
principle — compute the exact state of the system at time <i>t + 1</i>. I don’t
think the world is fully deterministic. I think that quantum mechanics tells us
that there is indeterminism at the microscopic level. Thus, while we can
compute, from the prior state, the <i>probability</i> of an atom decaying in a
given time interval, we cannot (even in principle) compute the actual time of
the decay. Some leading physicists disagree, and advocate for interpretations
in which quantum mechanics is deterministic, so the issue is still an open
question, but I suggest that indeterminism is the current majority opinion
among physicists and I’ll assume it here.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: Some kind of indeterminism does
indeed seem to be a majority view among physicists – I recorded an 80%
agreement in a decent-sized but entirely unscientific Twitter poll.
(Interestingly, the 80:20 split was the same among physicists and
non-physicists who responded). However, there is much less agreement on where
this indeterminacy comes from, how it should be interpreted, what it tells us
about the nature of reality, and what its effects might be at the classical
level.</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">This
raises the question of whether indeterminism at the microscopic level
propagates to indeterminism at the macrosopic level of the behaviour of
leopards. The answer is likely, yes, to some extent. A thought experiment of
coupling a microscopic trigger to a macroscopic device (such as the decay of an
atom triggering a device that kills Schrodinger’s cat) shows that this is
in-principle possible. On the other hand, using thermodynamics to compute the
behaviour of steam engines (and totally ignoring quantum indeterminism) works
just fine, because in such scenarios one is averaging over an Avogadro’s number
of partlces and, given that Avogadro’s number is very large, that averages over
all the quantum indeterminicity. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">What
about leopards? The leopard’s behaviour is of course the product of the state
of its brain, acting on sensory information. Likely, quantum indeterminism is
playing little or no role in the minute-by-minute responses of the leopard.
That’s because, in order for the leopard to have evolved, its behaviour, its
“leopardness”, must have been sufficiently under the control of genes, and
genes influence brain structures on the developmental timescale of years. On
the other hand, leopards are all individuals. While variation in leopard brains
derives partially from differences in that individual’s genes, Kevin Mitchell
tells us in his book <a href="https://www.amazon.co.uk/Innate-How-Wiring-Brains-Shapes/dp/0691173885"><i><span style="color: blue;">Innate</span></i></a> that development is a process
involving much chance variation. Thus quantum indeterminicity at a biochemical
level might be propogating into differences in how a mammal brain develops, and
thence into the behaviour of individual leopards. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">That’s
all by way of introduction. So far I’ve just defined and expounded on the
concepts “reductionism” and “determinism” (but it’s well worth doing that since
discussion on these topics is bedeviled by people interpreting words
differently). So let’s proceed to why I disagree with Mitchell’s account. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">He
writes: </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">For
the reductionist, reality is flat. It may seem to comprise things in some kind
of hierarchy of levels – atoms, molecules, cells, organs, organisms,
populations, societies, economies, nations, worlds – but actually everything
that happens at all those levels really derives from the interactions at the
bottom. If you could calculate the outcome of all the low-level interactions in
any system, you could predict its behaviour perfectly and there would be
nothing left to explain. </span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">There
is never only one explanation of anything. We can always give multiple
different explanations of a phenomenon — certainly for anything at the
macroscopic level — and lots of different explanations can be true at the same
time, so long as they are all mutually consistent. Thus one explanation of a
leopard’s stalking behaviour will be in terms of the firings of neurons and
electrical signals sent to muscles. An equally true explanation would be that
the leopard is hungry.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Reductionism
does indeed say that you could (in principle) reproduce the behaviour from a
molecular-level calculation, and that would be <i>one</i> explanation. But
there would also be other <i>equally true</i> explanations. Nothing in
reductionism says that the other explanations don’t exist or are invalid or
unimportant. We look for explanations because they are useful in that they
enable us to understand a system, and as a practical matter the explanation
that the leopard is hungry could well be the most useful. The molecular-level
explanation of “stalking” is actually pretty useless, first because it can’t be
done in practice, and second because it would be so voluminous and unwieldy
that no-one could assimilate or understand it.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: So, this is what I call the
ecumenical version of reductionism which comes in weaker or stronger forms. CH
states a weak form above – where he says that explanations at various levels
are equally valid. The physicist Sean Carroll espouses a similar view, but
states it in what is a subtly stronger (and kind of patronising) way – he describes
explanations at higher levels as <i style="mso-bidi-font-style: normal;">useful
ways <u>of talking about</u> complicated systems </i>– in effect, as convenient
fictions<i style="mso-bidi-font-style: normal;">. </i>But, he seems to insist
that <i style="mso-bidi-font-style: normal;">the real explanation</i> is at the
lowest level and a description at that level would be the most comprehensive
and would necessarily entail and explain all the higher-level organization and
apparent causality. (CH makes a somewhat similar argument below).</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">As
a comparison, chess-playing AI bots are now vastly better than the best humans
and can make moves that grandmasters struggle to understand. But no amount of
listing of low-level computer code would “explain” why sacrificing a rook for a
pawn was strategically sound — even given that, you’d still have all the
explanation and understanding left to achieve. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">So
reductionism does not do away with high-level analysis. But — crucially — it
does insist that high-level explanations need to be consistent with and
compatible with explanations at one level lower, and that is why the concept is
central to science.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell
continues:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">In
a deterministic system, whatever its current organisation (or “initial
conditions” at time t) you solve Newton’s equations or the Schrodinger equation
or compute the wave function or whatever physicists do (which is in fact what
the system is doing) and that gives the next state of the system. There’s no
why involved. It doesn’t matter what any of the states mean or why they are
that way – in fact, there can never be a why because the functionality of the
system’s behaviour can never have any influence on anything.</span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">I
don’t see why that follows. Again, understanding, and explanations and “why?”
questions can apply just as much to a fully reductionist and deterministic
system. Let’s suppose that our chess-playing AI bot is fully reductionist and
deterministic. Indeed they generally are, since we build computers and other
devices sufficiently macroscopically that they average over quantum
indeterminacy. That’s because determinism helps the purpose: we want the
machine to make moves based on an evaluation of the position and the rules of
chess, not to make random moves based on quantum dice throwing.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: There is a strong position in
physics and philosophy (espoused forcefully by Bertrand Russell, for example)
that argues that causes in fact do not exist. If the universe is really
deterministic, then there is no room for and no need for causes – understanding
and explanations and “why” questions absolutely would NOT apply. The universe
would simply evolve based on the initial conditions and the fundamental forces
determining the movements and interactions of all the particles. Determinism
thus implies reductionism. Something can only be considered a cause of
something else if it being different would have caused a difference to that
something else occurring. If there is no way that anything could actually be
different from how it is because the universe is evolving deterministically
from the dawn of time to the end of time (or indeed because it all just exists
in a block universe without a direction of time), then the concept of causation
simply does not apply. It relies on counterfactual possibilities being
ontologically real. (And so does the idea that information can have causal
power in a system).</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">But,
in reply to “why did the (deterministic) machine sacrifice a rook for a pawn”
we can still answer “in order to clear space to enable the queen to invade”.
Yes, you can also give other explanations, in terms of low-level machine code
and a long string of 011001100 computer bits, if you really want to, but
nothing has invalidated the high-level answer. The high-level analysis, the
why? question, and the explanation in terms of clearing space for the queen,
all still make entire sense.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: Now, here, as with many
compatibilist arguments or thought experiments, I think we need to back
waaaaaay up. The high-level explanation only applies in this thought experiment
because the computer was programmed by a human being <i style="mso-bidi-font-style: normal;">to do things for a reason</i>, and is playing a game developed by
humans that has goals and functionalities of components embedded in it. There’s
only an answer to the “why?” question because it was programmed in that way. If
you are going to posit determinism and try and deduce what follows from it,
then you don’t get to just assume the existence of games and computers and
computer programmers and go from there. You have to first explain how, in a
deterministic universe, <i style="mso-bidi-font-style: normal;">you would ever
get</i> games and computers and computer programmers. </span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">I
would go even further and say you can never get a system that does things under
strict determinism. (Things would happen in it or to it or near it, but you
wouldn’t identify the system itself as the cause of any of those things).</span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell’s
thesis is that you only have “causes” or an entity “doing” something if there
is indeterminism involved. I don’t see why that makes any difference. Suppose
we built our chess-playing machine to be sensitive to quantum indeterminacy, so
that there was added randomness in its moves. The answer to “why did it
sacrifice a rook for a pawn?” could then be “because of a chance quantum
fluctuation”. Which would be a good answer, but Mitchell is suggesting that
only un-caused causes actually qualify as “causes”. I don’t see why this is so.
The deterministic AI bot is still the “cause” of the move it computes, even if
it itself is entirely the product of prior causation, and back along a
deterministic chain. As with explanations, there is generally more than one
“cause”. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Nothing
about either determinism or reductionism has invalidated the statements that
the chess-playing device “chose” (computed) a move, causing that move to be
played, and that the reason for sacrificing the rook was to create space for
the queen. All of this holds in a deterministic world. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: Again, I question the validity
of the premises of this thought experiment. You have to explain how reasons
would ever come to be (how creatures that could have reasons would ever evolve)
in a deterministic universe or one where the only kind of causation at play is
at the lowest levels of physical forces (which as we’ve seen does not really
fit the concept of causation at all). Nothing would be <i style="mso-bidi-font-style: normal;">for anything – </i>you would have no purpose, no function, no value, no
goals, no meaning.</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell
pushes further the argument that indeterminism negates reductionism:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">For
that averaging out to happen [so that indeterminism is averaged over] it means
that the low-level details of every particle in a system are not all-important
– what is important is the average of all their states. That describes an
inherently statistical mechanism. It is, of course, the basis of the laws of
thermodynamics and explains the statistical basis of macroscopic properties,
like temperature. But its use here implies something deeper. It’s not just a
convenient mechanism that we can use – it implies that that’s what the system
is doing, from one level to the next. Once you admit that, you’ve left
Flatland. You’re allowing, first, that levels of reality exist.</span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">I
agree entirely, though I don’t see that as a refutation of reductionism. At
least, it doesn’t refute forms of reductionism that anyone holds or defends. Reductionism
is a thesis about how levels of reality mesh together, not an assertion that
all science, all explanations, should be about the lowest levels of
description, and only about the lowest levels. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: As I said above, the version of
reductionism I am thinking of (which despite CH’s assertion, many people do
indeed assert and seem to hold) is precisely the one that believes ultimately
“that all science, all explanations, should be about the lowest levels of
description, and only about the lowest levels”. More precisely and more fairly,
there are many people who assert the idea that <i style="mso-bidi-font-style: normal;">in principle</i> all the important business is happening at the lowest
levels, while allowing that <i style="mso-bidi-font-style: normal;">in practice</i>
it is not possible to fully describe complicated things at that level and so it
is much more convenient to work with measurable high-level coarse-grained
parameters. </span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">I said above that determinism
implies reductionism (no high-level causes, no causes at all, in fact, just the
wave function inexorably evolving). But I also claimed the converse, that
indeterminacy negates reductionism. This doesn’t obviously follow by necessity,
so let me explain the context of that claim. What I was trying to point out in
the original post was an inconsistency in the logic of people who allow that
quantum indeterminacy exists but claim that it would not percolate up to affect
classical levels. At the same time, they maintain a reductionist stance towards
explaining the behavior of complex systems and argue for determinism at the
classical level. If you admit that coarse-graining happens, from one level to
the next, and that not all of the details at the lowest level matter and that
many of those details have no effect on the system, then you have just rejected
reductionism. You’re not just thinking of the system <i style="mso-bidi-font-style: normal;">as a system</i> for convenience, you’re saying that its organization is
a key causal factor in its evolution, because this will determine which details
matter and which don’t. This is perfectly reasonable and correct, in my view, but
it’s no longer reductionist, at least not in a fully orthodox sense. If that
can happen from the quantum level to the next one up, then why couldn’t it
happen at every transition between levels where some coarse-graining occurs?
That would, in my view, be precisely what defines levels and grants them some
ontological validity.</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">So, there’s an “eating your cake,
and having it too” quality to that move – it basically invokes macroscopic
causation to reject an important role for quantum indeterminacy, while otherwise
claiming that all the causal work in complex systems occurs at the lowest
(classical) level and rejecting the idea that the organization of the system
embodies crucial causal relationships and criteria.</span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Indeterminism
does mean that we could not fully compute the exact <i>future</i> high-level
state of a system from the prior, low-level state. But then, under
indeterminism, we also could not always predict the exact future high-level
state from the prior <i>high-level</i> state. So, “reductionism” would not be
breaking down: it would still be the case that a low-level explanation has to
mesh fully and consistently with a high-level explanation. If indeterminacy
were causing the high-level behaviour to diverge, it would have to feature in
both the low-level and high-level explanations.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell
then makes a stronger claim:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">The
macroscopic state as a whole does depend on some particular microstate, of
course, but there may be a set of such microstates that corresponds to the same
macrostate. And a different set of microstates that corresponds to a different
macrostate. If the evolution of the system depends on those coarse-grained
macrostates (rather than on the precise details at the lower level), then this
raises something truly interesting – the idea that information can have causal
power in a hierarchical system …</span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">But
there cannot be a difference in the macrostate without a difference in the
microstate. Thus there cannot be indeterminism that depends on the macrostate
but not on the microstate. At least, we have no evidence that <i>that</i> form
of indeterminism actually exists. If it did, that would indeed defeat
reductionism and would be a radical change to how we think the world works.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">It
would be a form of indeterminism under which, if we knew everything about the
microstate (but not the macrostate) then we would have less ability to predict
time <i>t + 1</i> than if we knew the macrostate (but not the
microstate). But how could that be? How could we not know the macrostate? The
idea that we could know the exact microstate at time <i>t</i> but not be
able to compute (even in principle) the macrostate at the same time <i>t</i>
(so before any non-deterministic events could have happened) would indeed
defeat reductionism, but is surely a radical departure from how we think the
world works, and is not supported by any evidence.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">But
Mitchell does indeed suggest this:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">The
low level details alone are not sufficient to predict the next state of the
system. Because of random events, many next states are possible. What
determines the next state (in the types of complex, hierarchical systems we’re
interested in) is what macrostate the particular microstate corresponds to. The
system does not just evolve from its current state by solving classical or
quantum equations over all its constituent particles. It evolves based on
whether the current arrangement of those particles corresponds to macrostate A
or macrostate B. </span></span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">But
this seems to conflate two ideas:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">1)
In-principle computing/reproducing the state at time <i>t + 1</i> from the
state at time <i>t</i> (determinism).</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">2)
In-principle computing/reproducing the macrostate at time <i>t</i> from the
microstate at time <i>t</i> (reductionism).</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell’s
suggestion is that we cannot compute: {microstate at time <i>t</i> } </span><span style="font-family: "Menlo Regular"; font-size: 10pt; mso-ansi-language: EN-US;">⇒</span><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">
{macrostate at time <i>t + 1</i> }, but <i>can</i> compute: {macrostate at
time <i>t</i> } </span><span style="font-family: "Menlo Regular"; font-size: 10pt; mso-ansi-language: EN-US;">⇒</span><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> {macrostate at time <i>t + 1</i> }.
(The latter follows from: “What determines the next state … is [the] macrostate
…”.)</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">And
that can (surely?) only be the case if one cannot compute: {microstate at time <i>t</i> }
</span><span style="font-family: "Menlo Regular"; font-size: 10pt; mso-ansi-language: EN-US;">⇒</span><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> {macrostate at time <i>t</i> }, and if we are
denying <i>that</i> then we’re denying reductionism as an input to the
argument, not as a consequence of indeterminism. </span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: Okay, so this is the crux of the
argument and I really welcome the questioning, which will help me hopefully
clarify what I mean. It is not that knowing any particular microstate at time <i style="mso-bidi-font-style: normal;">t </i>would not also tell you the macrostate
at that time – it certainly would. It’s more a question of understanding the
full picture of causality in the system. The reason that any given microstate
will tend to lead to some subsequent microstate is by virtue of the macrostate
that it entails <i style="mso-bidi-font-style: normal;">meaning something</i>. </span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">The existence of indeterminacy makes
it possible – not inevitable, by any means, but possible – that systems could
evolve (which we call living organisms) that do have goals, purpose, value,
meaning, and function – that do things <i style="mso-bidi-font-style: normal;">for
reasons</i>. Those parameters are encoded at the level of macrostates. Of
course, at any given moment, they <i style="mso-bidi-font-style: normal;">are
realized</i> in some particular microstate, but the low-level details may be
incidental. Indeed, many aspects of the microstate of any given neuron or brain
region are lost or actively filtered out in the coarse-graining that happens
through synaptic transmission and population-level neural dynamics. It’s
meaning that drives the mechanism. </span></b></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></b></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">Mitchell
draws the conclusion:</span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="color: #2b00fe;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">In
complex, dynamical systems that are far from equilibrium, some small
differences due to random fluctuations may thus indeed percolate up to the
macroscopic level, creating multiple trajectories along which the system could
evolve. […]</span></span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">I
agree, but consider that to be a consequence of indeterminism, not a rejection
of reductionism. </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"><span style="color: #2b00fe;">This
brings into existence something necessary (but not by itself sufficient) for
things like agency and free will: possibilities.</span> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">As
someone <a href="https://coelsblog.wordpress.com/2014/12/03/compatibilism-for-incompatibilists-free-will-in-five-steps/"><span style="color: blue;">who takes a</span></a> compatibilist account of “agency” and
“free will” I am likely to disagree with attempts to rescue “stronger” versions
of those concepts. But that is perhaps a topic for a later post.</span></p><p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;"> </span></p>
<p class="MsoNormal" style="mso-margin-bottom-alt: auto; mso-margin-top-alt: auto;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "Times New Roman"; font-size: 10pt; mso-ansi-language: EN-US;">KM: To be clear, the arguments laid
out above are only making that case that indeterminacy is <i style="mso-bidi-font-style: normal;">necessary for</i> agency to exist (because it creates real possibilities
for agents to choose between, and because it opens the door to macroscopic
causation). How organisms have evolved to take advantage of that causal slack –
to become causes in their own right – is a much longer story, and the subject
of my next book ;-) With thanks again to Coel for the discussion. <br /></span></b></p>
<p class="MsoNormal"><br /></p><p class="MsoNormal"><span style="font-size: x-small;"><span style="font-family: times;">For more on that argument, see: Mitchell KJ. <a href="https://pubmed.ncbi.nlm.nih.gov/29961596/">Does Neuroscience Leave Room for Free Will?</a> Trends
Neurosci. 2018 Sep;41(9):573-576. doi: 10.1016/j.tins.2018.05.008. </span></span></p>
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{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-62893479235427026442020-12-12T10:36:00.004-08:002020-12-12T10:36:59.881-08:00Does freedom bubble up from the quantum realm? <p><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">I’ve been writing lately (in this <a href="https://www.sciencedirect.com/science/article/abs/pii/S0166223618301553">article</a> and <a href="http://www.wiringthebrain.com/2020/07/escaping-flatland-when-determinism.html">blogpost</a>, for example) about agency and
more specifically about whether neuroscience or basic physics rule out the idea
of free will, of organisms like us being able to genuinely make choices based
on their own reasons and thus act as causal agents in the world. I’m grateful
to Philip Goff for responding to some of these ideas in a recent <a href="https://conscienceandconsciousness.com/2020/12/11/does-quantum-mechanics-allow-for-free-will/">blogpost</a> and
to Philip Ball for continuing the conversation in <a href="https://philipball.blogspot.com/2020/12/does-quantum-mechanics-rescue-free-will.html">a post</a> of his own. </span></span></span>
</p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"></span></span><span style="font-family: arial;"><span lang="EN-GB"></span></span><span style="font-family: arial;"><span lang="EN-GB"></span></span><span style="font-family: arial;"></span><span style="font-family: arial;"></span><span style="font-family: arial;"><span lang="EN-GB">I respond to their arguments here and make
some more general points along the way. (For convenience, I will refer to the
two Philips by their last names, which feels a bit rude, so, sorry, Philips!). </span></span></span></p><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span><span style="font-family: arial;"></span><span style="font-family: arial;">
</span><span style="font-family: arial;"></span><span style="font-family: arial;"></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">The question that Goff takes up is my claim
that <b>fundamental indeterminacy at the quantum level creates some room in which
free will can operate</b>. He quotes the following passage, which sums up the
argument:</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"><br /></span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span lang="EN-GB">“The
inherent indeterminacy of physical systems means that any given arrangement of
atoms in your brain right at this second, will not lead, inevitably, to only
one possible specific subsequent state of the brain. Instead, multiple future
states are possible, meaning multiple future actions are possible. The outcome
is not determined merely by the positions of all the atoms, their lower-order
properties of energy, charge, mass, and momentum, and the fundamental forces of
physics. What then does determine the next state? What settles the matter?”</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">To
be clear, this line of thinking does not originate with me. It’s been well
explicated by people like <a href="https://en.wikipedia.org/wiki/George_F._R._Ellis">George Ellis</a> and <a href="https://ahc.leeds.ac.uk/philosophy/staff/1167/professor-helen-steward">Helen Steward</a> in recent times, but
really dates back to the ancient Greeks, most notably <a href="https://plato.stanford.edu/entries/epicurus/">Epicurus</a> (some of whose
work was effectively reproduced by the Roman philosopher <a href="https://en.wikipedia.org/wiki/Lucretius">Lucretius</a>, in the form
of his didactic poem <a href="https://en.wikipedia.org/wiki/De_rerum_natura">De Rerum Natura</a> (On the Nature of Things)). <span> </span></span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><span style="font-size: small;"><span style="font-family: arial;"></span></span><span style="font-size: small;"><span style="font-family: arial;"></span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"><br /></span></span></span></p><span style="font-size: small;"><span style="font-family: arial;"></span></span><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"></span></span></span><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">One
of the most <a href="https://www.academia.edu/4309985/Epicurus_refutation_of_determinism">important arguments</a> that Epicurus makes invokes what is now known
as “the swerve”. Epicurus inherited from <a href="https://en.wikipedia.org/wiki/Democritus">Democritus</a> and his followers the remarkably
prescient idea that all matter was composed of simple particles (which
Democritus had called “atoms”) and that complicated stuff was made of different
combinations of such atoms. But he objected to the rigidly deterministic laws
that Democritus had developed to explain how atoms move and what happens when
they collide. He famously argued that if there were no element of randomness in
the movements of atoms – if they did not occasionally “swerve” – then, first of
all, the universe would not exist (which feels like a biggie), and, secondly,
that humans, or any animal, would be incapable of autonomous action or real choice.
</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">In
modern parlance, if we are made of atoms and their movements are entirely
determined by the low-level laws of physics, then the atoms are gonna do what
the atoms are gonna do. It doesn’t matter what we want – indeed, wanting would
never arise – why would it? Alternate possibilities would simply not exist.
Everything would be determined in an unbroken line from the beginning of the
universe to the end of time. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">The
swerve – that element of randomness – breaks that chain and introduces freedom
and indeterminacy into the universe. It creates possibilities where none would
exist without it. But Epicurus’ target was not just determinism – he <a href="https://www.academia.edu/4309985/Epicurus_refutation_of_determinism">also argued</a> forcefully against <b><i>reductionism</i></b>, the idea that the
origins of causal power, even in complex systems like living organisms, are
ultimately entirely traceable to the forces controlling the movements of atoms.
He recognised that this idea is incompatible with the autonomy of living beings,
including humans. <span> </span></span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">His
argument (and mine) is thus not simply that the world has some randomness in
it. Many people rightly point out that randomness by itself does not provide
free will. The argument goes that if my decisions are fully <i>pre</i>-determined by the laws of physics,
then they are not freely made by me. But if they are determined, in the act of
making a decision, by random swerves of atoms in my brain, then they are also
not freely made <i>by me</i>. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">This
is true, but it ignores Epicurus’ wider point – that the existence of some
randomness at the lowest levels means that <i>causality
does not fully inhere at those levels</i>. Instead, the higher-order
configuration of a system can play a causal role in its evolution from state to
state. (In other words, when determinism falls, <a href="http://www.wiringthebrain.com/2020/07/escaping-flatland-when-determinism.html">reductionism falls with it</a>).</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">This
is the argument I have been making too, updated with reference to our modern
understanding of fundamental physics (and neuroscience, genetics, and
evolution). Epicurus’ swerve has a modern echo in the indeterminacy inherent in
<a href="https://en.wikipedia.org/wiki/Quantum_mechanics">quantum theory</a> and empirically observed in events at quantum levels. (Though
there are multiple different interpretations of what the quantum theory means
for the ultimate nature of reality).</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">The
question that Goff and Ball take up is whether this quantum indeterminacy
really leaves room for or rescues free will. (As an aside, I don’t think free
will needs “rescuing” – the fact that we make decisions is one of the most
basic aspects of our experience. It’s what we do all day, every day – go around
making one choice after another. Any claim that this deepest aspect of the
phenomenology of our existence is an illusion should in my view carry a heavy
burden of proof).</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">Goff
takes this indeterminacy (and my position of incompatibilism) for granted for
argument’s sake, but says:</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span lang="EN-GB">“It
sounds intuitive, but I don’t think this strategy ultimately works. Even among
indeterministic interpretations of quantum mechanics, although the physics
doesn’t conclusively settle what will happen, it does determine the <em>objective
probability</em> of what will result from any given physical
circumstance. Although we can’t predict with certainty, say, where a given
particle will be located when we make a measurement, the Born rule tells us,
for any given location in the universe, precisely how likely we are to find the
particle in that location. It’s not determinism, but it’s not a ‘free for
all.’”</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">He
goes on to imagine a scenario where the Born rule plays a role in determining
the “objective probability” of his own macroscopic actions:</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p><span style="font-family: times;"><span style="font-size: small;"><span>“Mitchell worries that if the physics
determines what I’m going to do, then I’m not really free. But physics
determining the <em>objective probability</em> of what I
will do is no less constraining. If whether I water Susan (my Madagascan dragon
tree) is really up to me – in the strong incompatibilist sense – then surely
the physics can’t fix <em>how likely </em>it is that
I will water Susan. If it’s just totally up to me, then it could go either way
depending on my radically free choice.</span></span></span></p><span style="font-family: times;"><span style="font-size: small;">
</span></span><p><span style="font-family: times;"><span style="font-size: small;"><span>Here’s a little thought experiment to make
the point clear. Take the moment when I’m about to decide whether or not to
water Susan. Let’s say the Born rule determines that there’s a 90% chance my
particles will be located in the way they would be if I watered Susan and a 10%
chance there’ll be located in the way that corresponds to not watering Susan
(obviously this is a ludicrously over-simplistic example, but it serves to make
the point). </span><span>Now imagine someone duplicated me a million
times and waited to see what those million physical duplicates would decide to
do. The physics tells us that approximately 900,000 of the duplicates will
water Susan and approximately 100,000 of them will not. If we ran the
experiment many times, each time creating a million more duplicates and waiting
for them to decide, the physics tells us we would get roughly the same
frequencies each time. But if what happens is totally up to each duplicate – in
the radical incompatibilist sense – then there ought to be no such predictable
frequency. The number that do and don’t water the plant should change each
time, as the radically free choices of each individual varies.</span><span>”</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">My
first reaction to this is similar to the main point that Ball makes in his own
commentary – namely, that it is an ill-posed thought experiment. The <a href="https://en.wikipedia.org/wiki/Born_rule">Born rule</a>
applies to quantum events and elementary particles, not to macroscopic objects
and certainly not to the decision-making of agents. Moreover, it applies <i>independently</i> to single particles and
events (unless they are entangled). So, in a complex system, all those
probabilities will multiply exponentially to create a massive web of
indeterminacy. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">This
is the main point of my argument. The quantum events do not decide the outcome
– they merely make the whole system indeterminate. This has two key
implications: the next state of the system is <i>NOT</i> determined by the current state
plus the laws of physics. And the causal influences are <i>NOT</i> restricted to the
lowest level of the system. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">I
also do not see what the idea of “<i>objective</i>”
probabilities of various outcomes being determined by physics is doing in this
argument. The whole idea of probability is open to many different
interpretations and it’s not clear at all that there is, or should be, a
straightforward mapping of its meaning at the level of quantum events to its
meaning at the level of human choices. These levels are simply incommensurate. As
Ball says, “It’s best, I think, to explain phenomena at the
conceptual/theoretical level appropriate to it.”</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">The
important point is that <i>possibilities</i>
exist – they don’t have to be equally likely. Indeed, it will almost always be
the case that you won’t weight the choices open to you equally. I don’t think
anything in particular follows from that. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">Goff
follows up with a broader point, which is interesting, though I’m struggling to
fully grasp what he means by it: </span></span></span></p><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span>“All is
not lost, however. I think Mitchell is conflating two claims:</span></span></span></p><span style="font-family: times;"><span style="font-size: small;">
</span></span><ul type="disc"><li class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span>The <i>laws of physics</i> are deterministic</span></span></span></li><li class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span>The <i>universe as a whole</i> is deterministic</span></span></span></li></ul><span style="font-family: times;"><span style="font-size: small;">
</span></span><p class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span>How
could these come apart? They come apart if the laws of physics are <i>ceteris
paribus </i>laws, i.e. laws that tell us <i>what will happen in the absence of
other causal influences</i>. On this interpretation of physical law, the
probabilities yielded by the Born rule are the objective probability of what
will occur <i>in the absence of some other causal influence</i>. Such other
causal influences might include the kind of irreducible causal powers Mitchell
believes reside at the level of neurobiology. Mitchell seems to be concerned to
avoid a violation of the laws of physics. But if the laws of physics are
ceteris paribus laws, then higher-level causal powers should be thought of as <i>complimenting
</i>the laws of physics rather than contradicting them. If physics basically
tells us ‘X will happen unless there are some higher-level causal forces,’ and
X doesn’t happen precisely because there <i>are</i> higher-level causal forces,
then nothing occurs that is inconsistent with physics.”</span></span></span></p><p class="MsoNormal"><span style="font-family: times;"><span style="font-size: small;"><span> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">I think I kind of agree with this, though I
might not word it like that. I do think there are other kinds of causal forces
at work, which constrain and inform how the physical state of our brains
evolves from moment to moment. In particular, I have argued (in this <a href="https://www.youtube.com/watch?v=3FL1xBX-dz4">recent talk</a>, for example, or this <a href="https://www.facebook.com/watch/?v=648471095910764">longer one</a>) that what drives
the next state is the <i>meaning</i> of the
current state (or the meanings, plural, of all the sub-states across the brain),
which is instantiated in the configuration of the neural circuitry and the
history that it embodies. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">But I would argue that such an effect or
interpretation is only possible <i>because</i>
the laws of physics are not deterministic. If they were, then the universe
would be deterministic and they would not be ceteris paribus (all other things
being equal) laws. There would be, indeed could be, no “other things”, from a
causal perspective. (At least, that’s my strong intuition, but I’d be very
interested to hear what others, especially physicists or philosophers make of
the idea).</span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB">Thankfully, it seems that indeterminacy
does exist (at least according to a majority interpretation of the current
knowledge of physics). Epicurus was right – the atoms (or more fundamental
particles) do seem to swerve every now and then. And life, agency, and yes, even
what we call free will, can evolve in the causal spaces created by those
swerves. </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: arial;"><span lang="EN-GB"> </span></span></span></p><span style="font-size: small;"><span style="font-family: arial;">
</span></span><p><style><font size="3"><span style="font-family: arial;">
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ul
{margin-bottom:0in;}</span></font></style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-79131932389588872322020-11-22T11:45:00.002-08:002020-11-22T11:45:29.823-08:00A sinister attractor – why males are more likely to be left-handed <p class="MsoNormal"><span lang="EN-GB"></span><span lang="EN-GB">It seems an innocent enough question: why are
males more frequently left-handed than females? But the answer is far from simple,
and it reveals fundamental principles of how our psychological and behavioural
traits are encoded in our genomes, how variability in those traits arise, and
how development is channelled towards specific outcomes. It turns out that the
explanation rests on an underlying difference between males and females that
has far-reaching consequences for all kinds of traits, including
neurodevelopmental disorders. </span></p><p class="MsoNormal"><span lang="EN-GB"> <table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh7rAmrK1I6yMc95UA7vAH8LTwjeQBCbJDGRw9r8jyGejamPd7co4mibDbiD_UXULiRyW-zaNkkpMjjBoXKOgU9KV5tJFPDELonfDv8FHpNZhFKSyRSs_SmN9CPteHh0eXtCxaANX-sVCl7/s1280/left+hand.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="856" data-original-width="1280" height="268" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh7rAmrK1I6yMc95UA7vAH8LTwjeQBCbJDGRw9r8jyGejamPd7co4mibDbiD_UXULiRyW-zaNkkpMjjBoXKOgU9KV5tJFPDELonfDv8FHpNZhFKSyRSs_SmN9CPteHh0eXtCxaANX-sVCl7/w400-h268/left+hand.png" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Pixabay.com<br /></td></tr></tbody></table><br /></span>
</p>
<p class="MsoNormal"><span lang="EN-GB">A <a href="https://twitter.com/dr_appie/status/1328578567987400705">recent tweet</a> from Abdel Abdellaoui showed
data on rates of left-handedness obtained from the UK Biobank, and asked two
questions: why is left-handedness more common in males and why are rates of
reported left-handedness increasing over time? </span></p><p class="MsoNormal"><span lang="EN-GB"></span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHnPfCX_4XdP_6zEj4C61HuPp9AcVwfsggCd-FjPrYJU7V_-8DdTw0dGMqWVwoOppT1yIPMzHL_DvPVoklLUkuTFhPJCyIdEZcIeC37_0MynJRqCJ1Rt_Xn4enOiY2BEdf14M50WQyrfPo/s1047/lefties-UK+biobank+data.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="847" data-original-width="1047" height="518" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHnPfCX_4XdP_6zEj4C61HuPp9AcVwfsggCd-FjPrYJU7V_-8DdTw0dGMqWVwoOppT1yIPMzHL_DvPVoklLUkuTFhPJCyIdEZcIeC37_0MynJRqCJ1Rt_Xn4enOiY2BEdf14M50WQyrfPo/w640-h518/lefties-UK+biobank+data.png" width="640" /></a></div><p>I don’t think the answer to the second
question is known but I presume it has to do with the declining practice of
forcing left-handers to write right-handed. This once common practice reflects a
long history of prejudice against lefties, illustrated by the derivation of the
word “sinister”, which in Latin means “left”, as opposed to “dexter” meaning
“right” which is the root of the positive words “dexterity” and “dextrous”. </p><p></p>
<p class="MsoNormal"><span lang="EN-GB">The first question – why is left-handedness
more common in males? – is the one I want to explore here, as it opens up some
fascinating questions about robustness, variability, and developmental
attractors. This is a long known and extremely robust finding. Rates of
left-handedness (from this UK sample) are around 11-12% in males and 9-10% in
females and these kinds of differences are seen across cultures and across time. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Why would this be? For that matter, why do
we even have handedness? Why is there a bias towards <i style="mso-bidi-font-style: normal;">right</i>-handedness? And does this sex difference tell us anything
about how handedness emerges or about sex differences in neural or behavioral
traits more generally?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Handedness is not unique to humans – many
animals show a preference for using one hand over another for (ahem) dextrous
movements. (Not so much for big movements or lifting heavy things, but for
actions requiring fine motor control). This may reflect the wiring and
communication demands of such actions. For fine motor sequences that have to be
carried out quickly, it may be much more efficient to code them all in a
concentrated area of neural tissue. In the brain, this means avoiding having to
communicate back and forth between the two hemispheres. The result is that the
neural substrates of fine motor sequences tend to get concentrated in one
hemisphere. This may be why control of speech, which involves very
sophisticated motor programs, tends to be localised to one hemisphere.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What’s less obvious is why there should be
a bias to consistently localise such functions to <i>one specific</i> hemisphere
versus the other. One possible explanation is that biasing the process
consistently towards one side or the other might make the outcome of hand
preference generally more robust. Maybe getting rid of the need to “choose” one
side or the other at some stage of development removes a possible failure point
from the overall process. (That’s admittedly super speculative, on my part). Others
have proposed a variety of social explanations for a consistent directional
bias. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"><br />
</span></p>
<p class="MsoNormal"><span lang="EN-GB"></span><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Patterning
the left-right axis</span></b>
</p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In any case, in order for the two
hemispheres to develop different patterns of neural circuitry (or for our
internal organs to be patterned and positioned asymmetrically), the developing
embryo must have some systems for distinguishing left from right. In
particular, it requires a symmetry breaker, based on something intrinsic in the
embryo. The <a href="https://f1000research.com/articles/9-123/v1">details of how this happens</a> differ between species, but the
mechanism ultimately seems to go all the way down to the level of the <a href="https://en.wikipedia.org/wiki/Chirality">chirality</a>
of various protein molecules, often with some function in the cytoskeleton or
cilia motility. After this initial symmetry breaking process, a much more
conserved set of signaling pathways is involved in mediating the subsequent differentiation
of the left and right sides of the developing embryo, ultimately including the
brain.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, there are genetic processes that reliably
code for hand preference (presumably by controlling aspects of neural
development that differ between the hemispheres) that may be ancient and found
in many animals. And there seem to be <i style="mso-bidi-font-style: normal;">separate</i>
genetic processes that code for the rightward bias, which may be more unique to
humans (but for findings from other animals see <a href="https://www.tandfonline.com/doi/abs/10.1080/1357650X.2012.723008?casa_token=cMbtfP97n7MAAAAA%3Ap9TugmiYtcXSP16SOUcDt5JZbQLLA39H5rp6yVeV9Yh-nXmZVh7knpFfEjiyv1QwBGacPezfWg6mdQ&journalCode=plat20">here</a> and <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351643/">here</a>).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But why is this rightward bias not 100%?
There are two possible reasons: one, a certain rate of left-handedness may be
evolutionarily selected for. That is, in a game theory sense, it may be
beneficial to be left-handed when most other people are right-handed (in
hand-to-hand combat, for example), but once the frequency of left-handedness
starts to increase, that advantage decreases. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p><span lang="EN-GB">The alternative is much more prosaic: a
certain rate of left-handedness may simply reflect the fact that any
genetically encoded process will show some variation, unless that variation
literally kills you. (My money is on this explanation because it doesn’t
require any additional special reasons).</span></p><p><span lang="EN-GB"> </span> <br /></p><p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
genetics of handedness</span></b></p><p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB"> </span></b></p>
<p class="MsoNormal"><span lang="EN-GB">Whether it’s actively selected for, or just
not actively selected against, if genetic variation affects the trait, this
means left-handedness should run in the family, and indeed it does. The general
rate of left-handedness is about 10%, but if one of your parents is
left-handed, then <a href="https://www.amazon.co.uk/Right-Hand-Left-Asymmetry-Cultures/dp/0674016130">your chance of being left-handed</a> is about 15%. If both of
your parents are left-handed, that rate rises to over 20%. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">Very large-scale <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2755095/">twin and family studies</a>
have estimated the heritability of handedness at about 25%. That means, across
the population, about a quarter of the variance in handedness is due to genetic
differences between people. Recent genome-wide association studies have had
some success in <a href="https://pubmed.ncbi.nlm.nih.gov/32989287/">identifying genetic variants</a> that predispose (very weakly) to
left-handedness. Some <a href="https://www.biorxiv.org/content/10.1101/454660v1">enrichment</a> of genes encoding cytoskeletal proteins seems
congruent with the known cellular mechanisms of left-right patterning (but
frankly it’s early days with these studies).</span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The important thing here is that the
inheritance of left-handedness is <i style="mso-bidi-font-style: normal;">probabilistic</i>.
In fact, you don’t inherit left-handedness – you inherit a certain <i style="mso-bidi-font-style: normal;">likelihood</i> of being left-handed. We can
see that this probability plays out independently, even in monozygotic twins.
If one twin is left-handed, the chance of the other being left-handed is <a href=" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900763/">only about 25%</a> (a good bit higher than the population average but obviously much
less than 100%).</span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So what other factors determine how this
genetic likelihood plays out? Could our upbringing have an effect? Well, most
parents will probably recognise that the handedness of their children is not
something they had any influence over. And the twin and family studies bear
this common experience out – they have consistently found no effect at all of
the family environment on handedness. Nor have any systematic factors in the
wider environment been reliably associated with handedness. </span>
</p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If it’s not genes and not environment, what
else could be affecting this trait? Well, there is a third source of variation
that is extremely important, though often overlooked, which is <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">development
itself</i></b>. As I have written about extensively (including in my book,
“<a href="https://press.princeton.edu/books/hardcover/9780691173887/innate">Innate</a>”), the processes of development are noisy, in engineering terms. What
is encoded in the genome is not a highly specified outcome but rather a set of
biochemical rules that underpin the processes of development. When played out,
these mindless biochemical algorithms will tend (quite robustly) to produce an
outcome within a well-functioning range. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Natural selection frankly doesn’t care that
much about all the details – the thing just has to work. The consequence of the
inherent noisiness of developmental processes is that every time you run the
developmental program from any particular genome, you get a unique outcome. For
many traits (like height, for example, or facial morphology), this
developmental variation manifests quantitatively. For traits like handedness,
however, which is effectively dichotomous, it manifests probabilistically.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">A rolling
stone</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A useful way of thinking about this is
provided by the visual metaphor of the “epigenetic landscape”, introduced by
<a href="https://www.amazon.co.uk/Strategy-Genes-Routledge-Library-Editions/dp/1138017310">Conrad Waddington in 1957</a>. The idea is that a developing organism (the ball)
is channelled along certain phenotypic trajectories as it proceeds through
development. The shape of the landscape and the relative depth of these
channels is determined by the genetics of the individual. </span></p>
<p class="MsoNormal"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicK5Hl4izZ0lks3mrpBhtso0vSX2cn5AlTJsW8px2wIdAvXJnFdD-xattJQAbvQlqgKN3BTlGlFVeQ_dTiZuuuC4xEUgzyW7THi-IC8alJjhsW25gLdOiKytAIQAoWF_qvz5V3nntwiJ20/s890/Epigenetic+landscape.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="320" data-original-width="890" height="230" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicK5Hl4izZ0lks3mrpBhtso0vSX2cn5AlTJsW8px2wIdAvXJnFdD-xattJQAbvQlqgKN3BTlGlFVeQ_dTiZuuuC4xEUgzyW7THi-IC8alJjhsW25gLdOiKytAIQAoWF_qvz5V3nntwiJ20/w640-h230/Epigenetic+landscape.jpg" width="640" /></a></div><br /><br />
<p class="MsoNormal"><span lang="EN-GB">For a landscape derived from an “average”
genome, it should be less likely for the ball to roll into the channel that leads
towards left-handedness than the one towards right-handedness. If you run 100
balls over this landscape, on average only 10 of them would end up in the lefty
channel, while 90 would end up in the righty channel. But if you generated the
landscape from the genome of someone who is actually left-handed, the channel
towards left-handedness would be easier to get into, and the outcome of 100
balls might be 25:75. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Whatever the shape of the underlying
landscape, the actual outcome in any individual would depend on a significant
element of <i style="mso-bidi-font-style: normal;">chance</i>. At some point in
development, represented by the arrows in the diagram, a small amount of noise
might nudge the ball towards one or other trajectory. The self-organising
processes of development would then reinforce that choice to ultimately produce
dichotomous outcomes. In the parlance of dynamical systems, left- and
right-handedness are two distinct phenotypic <a href="https://en.wikipedia.org/wiki/Attractor">attractors</a>. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The development of handedness may rely on
processes that act like a switch. We saw above that it is important to localise
fine motor control to one side of the brain or the other. It may not matter
that much whether it’s left or right – what you want to avoid is failure to
localise it at all. Left- or right-handedness may thus represent mutually
exclusive – even possibly antagonistic – developmental trajectories. “Choosing”
one pathway may inhibit the other and reinforce itself. This view is consistent
with the fact that left-handedness is <a href="https://en.wikipedia.org/wiki/Handedness">much more common</a> (and thus presumably
much better tolerated) than either mixed handedness or non-handedness.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">What this all means is that, though
handedness is only partly heritable, it may be <b>largely or even completely
innate</b>. (As an aside, a similar situation may hold for other traits, such as
<a href="http://www.wiringthebrain.com/2014/03/gay-genes-yeah-but-no-well-kind-of-but.html">sexual preference</a>). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Now, back to the question we started with –
why should <i style="mso-bidi-font-style: normal;">sex</i> affect the outcome of
development with respect to handedness? What is about the way males develop
that would lead them to end up left-handed more frequently, and why should
things be this way? There are many scenarios one could come up with that invoke
some sort of special connection between sex and handedness, maybe involving
sexual selection, males with rare phenotypes having an advantage, and so on.
These all seem very speculative to me and I don’t think we need to posit any
such mechanisms. A more likely explanation to me, and one that is certainly
more parsimonious, is that the increased rate of left-handedness reflects the
greater male variability that is observed in many traits, not just in humans,
but in many other animals too. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Greater
male variability</span></b></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Males show a small but statistically
significantly higher variance than females for all kinds of traits in humans.
The spread of values is <a href="https://pubmed.ncbi.nlm.nih.gov/19031491/ ">greater in males</a> for birth weight, morphological
traits, a range of blood parameters, and even things like athletic and academic
performance. The <a href="https://pubmed.ncbi.nlm.nih.gov/26158978/">same is true for IQ</a>, with males showing a wider, flatter curve than
females, with a consequently greater proportion of males at both the low and
high ends. There are <a href="https://pubmed.ncbi.nlm.nih.gov/33198888/">similar findings in mice</a>, especially for morphological traits, though
females showed a greater variance in immunological measures, possibly due to
fluctuating hormonal influences.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">You can see this kind of variability play
out within an individual too, across the two sides of the body (which represent
largely independent “runs” of the same genomic program). Males show higher
levels of “fluctuating” (i.e., random) <a href="https://pubmed.ncbi.nlm.nih.gov/22702244/">asymmetry of facial morphology</a> than
females.
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Why would this be? Well, first, the fact
that this trend is observed across species argues strongly against a cultural
origin for it, though initial biological differences might well be amplified
through cultural mechanisms in humans. But what would cause it in the first
place? We might look to hormonal influences – maybe testosterone just plays
havoc with the precision of developmental programs, for example. But as we will
see below, the same phenomenon is observed in insects where sex hormones play
no role in morphological differentiation. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Something more fundamental is going on and
it can be traced to the sex chromosomes – in particular, to the fact that males
in mammals have only one copy of the X chromosome, while females have two. Genetic
variation on the X chromosome will therefore have a bigger phenotypic effect in
males, not just for single loci, but as a collective effect. <a href="https://pubmed.ncbi.nlm.nih.gov/24299417/">This paper</a> by
Reinhold and Engqvist sums it up nicely:</span></p>
<p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span lang="EN-GB"> </span></p><span style="font-size: small;">
</span><p class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;"><span lang="EN-GB" style="font-size: small;">“</span><span style="font-family: "Times New Roman"; font-size: 9.5pt; mso-ansi-language: EN-US;"><span style="font-size: small;">In females, the traits
that are influenced by X chromosomal genes will be under the average influence
of the two parental copies, whereas in males, the effect of the single
X-chromosome will not be averaged. As a result, male mammals are expected to
show larger variability than females in all traits that are, at least to some
extent, influenced by X-chromosomal alleles.” </span>
</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is not to suggest that all the traits
mentioned above are X-linked, in the normal sense of that term. In fact, they
are all highly polygenic, involving genes all over the genome. It is just that
some of those genes are on the X chromosome and variation in such genes will be
averaged out or buffered more in females than in males. Because the buffering
of genetic variation is a little less efficient or robust in males, the
variance of the traits will be consequently greater. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Now, the hypothesis that this effect is due
to the number of X chromosomes, rather than effects of male hormones, makes a
strong prediction, which <a href="https://pubmed.ncbi.nlm.nih.gov/24299417/">Reinhold and Engqvist tested beautifully</a>, taking
advantage of the fact that in some species females are the ones with two
different sex chromosomes. This is the case in many bird species, where males
have two Z chromosomes and females have a Z and a W. A similar situation holds
in butterflies. But most mammals and many insects have an XX (female) and XY
(male) arrangement. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The prediction is that in such species, the
effect should be reversed – females should be more variable. Looking across
many different species of mammals, birds, butterflies, and insects, a pattern
consistent with the sex-chromosome hypothesis was found: the sex with two
different sex chromosomes was more variable. (As an aside, this paper is a
wonderful example of how to do science – an insightful and bold prediction,
allowing a stern test of a hypothesis, with painstaking research to follow it
up). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><div class="separator" style="clear: both; text-align: center;"><span lang="EN-GB"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgD7LwL0G5oofFIsZTk6e5HX1S2JblixtSWsPGUJNooax6YkpNtka8PvzS8iiEtMzEtkg4QcnWeboTdsUnOKQ8unIJyJ4gJrVZOiuNW1N9hBy_UB72kMBFDEHiooOzNuZu0GrB0ncb9gdaO/s1108/Reinhold+figure.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1032" data-original-width="1108" height="373" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgD7LwL0G5oofFIsZTk6e5HX1S2JblixtSWsPGUJNooax6YkpNtka8PvzS8iiEtMzEtkg4QcnWeboTdsUnOKQ8unIJyJ4gJrVZOiuNW1N9hBy_UB72kMBFDEHiooOzNuZu0GrB0ncb9gdaO/w400-h373/Reinhold+figure.png" width="400" /></a></span></div><span lang="EN-GB"><br /></span><p></p>
<p class="MsoNormal"><span lang="EN-GB">Okay, back to humans. One way to interpret
the observation that males are more variable is that they are less robustly
channelled into narrow phenotypic outcomes. As discussed above, this will
mostly manifest as quantitatively greater variance for all kinds of traits. For
handedness, it should mean that developing male organisms are less strongly
channelled into the trajectory leading to right-handedness. In our visual
metaphor, this may mean a slightly lower ridge between the channels for a
longer time or generally a flatter plain preceding the important choice point.
Development in males should be just a little noisier and all the feedback loops
that normally ensure robust development should be just a little less able to
buffer that noise. In effect, male embryos may be slightly more likely to
jiggle into the left-handed channel. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">[Note: I’d love to try and formalise those
intuitions or even have a virtual marble run to play with parameters in, if there are any modellers out there who’d fancy having a go].</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If this were just about handedness, it’d be
a cute story, but maybe just a curiosity. But we can see the same effect on
other phenotypes, including susceptibility to neurodevelopmental disorders.
Males have <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507200/">substantially higher rates of diagnosis</a> of a range of such
disorders, including autism, ADHD, schizophrenia, stuttering, tic disorders,
and others. These conditions can be <a href="https://www.biorxiv.org/content/10.1101/009449v1">caused by rare mutations</a> in any of a very
large number of different genes, with complicated polygenic background effects
at play. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A now <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951938/">well-replicated finding</a> is that
females with such diagnoses have <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904808/">more serious mutations</a> on average than males
do. This suggests that it takes a bigger mutation to push a developing female
brain into one of these phenotypic outcomes, while developing male brains are
less able to buffer the effects and therefore more vulnerable. Consistent with
this view, when such mutations are inherited from a parent (as opposed to
arising de novo in the generation of sperm or eggs), they have been found to be
more likely to have been inherited from the mother. One interpretation of that
result is that males who had such a mutation would have been more severely
affected and thus less likely to have children, while females are better able
to buffer the effects. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">See what happens when you ask a seemingly
innocent question? ;-)</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p><style>
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div.WordSection1
{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-34836670390524203412020-09-30T01:03:00.000-07:002020-09-30T01:03:00.606-07:00Corvid consciousness – computation, cognition, or comprehension?<p class="MsoNormal"><span lang="EN-GB"></span><span lang="EN-GB">A <a href="https://science.sciencemag.org/content/369/6511/1626">really nice paper</a> came out recently that
claims to </span><span lang="EN-GB"></span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiJLxo03An9G7Dm16Fdm9HHiHsN4dofTCS6ZIurF8CvaOLtuQ66lQ7ZFsDGBKUdOqURu4qYOhv8m3vIN4-0-KfuWDttVEJW8Hk9tXcatjOKTWR-JmGABjM57Bb8saezinn7Mfj0U4hBfwJy/s1168/crow.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="1149" data-original-width="1168" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiJLxo03An9G7Dm16Fdm9HHiHsN4dofTCS6ZIurF8CvaOLtuQ66lQ7ZFsDGBKUdOqURu4qYOhv8m3vIN4-0-KfuWDttVEJW8Hk9tXcatjOKTWR-JmGABjM57Bb8saezinn7Mfj0U4hBfwJy/s320/crow.jpg" width="320" /></a></div><span lang="EN-GB">have discovere</span><span lang="EN-GB"></span><span lang="EN-GB">d a ne</span><span lang="EN-GB"></span><span lang="EN-GB">ural correlate of sensory consciousness in a
corvid bird (the carrion crow). The authors use an elegant set up involving
barely perceptible visual stimuli to distinguish the delivery of a stimulus and
the s</span><span lang="EN-GB"></span><span lang="EN-GB">ubjective percept that it engenders. The experiment clearly
demonstrates that crows can maintain an internal representation
for a period of time before taking an action based on a rule that is
subsequently presented to them. This kind of task has been used in primates to
distinguish what happens in the brain when an animal consciously detects a
stimulus versus when it doesn’t. But is this really a correlate of conscious
subjective experience or simply a marker of ongoing neural activity that
mediates working memory? What do we even mean by conscious subjective
experience? Does maintaining an active neural state necessarily entail a mental
state?<br /></span>
<p></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The experimental set up is really powerful.
The authors trained two crows to perform this behavioral task while recording
from hundreds of neurons in a particular part of the bird brain that is thought
to be analogous to the mammalian <a href="https://en.wikipedia.org/wiki/Prefrontal_cortex">prefrontal cortex</a>. The birds are either shown
a stimulus or not, for a very brief time – so brief that they sometimes detect
it and sometimes don’t. Whether they do or not is determined in some way by the
current internal state of the crow’s brain (this may reflect the precise phase of
<a href="https://pubmed.ncbi.nlm.nih.gov/25400608/">rhythmic patterns</a> of ongoing neural activity and excitability at the moment of
stimulus presentation).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">After a brief period, the crows are then
presented with a rule, which tells them how they should act in response to
either the presence or absence of a stimulus. This means that the crow must
maintain some sort of internal representation for some period of
time while waiting to be told what to do with that information.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The important thing about this set up is
that it dissociates the presence of the stimulus with the percept of the
animal. In particular, the crows <i>can be wrong</i> in two ways – they can fail to
see something when a stimulus was actually presented, or they can think they
saw something when no stimulus was presented, leading to a distinction between direct visual stimulation and subjective experience.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In primates, including humans, you get
quite different brain responses on trials when the subject reports (either by
behavior or by language) that they consciously saw something versus when they
didn’t. Neurons in primary visual cortex respond to a visual stimulus whether
the animal “sees” it or not. Trials where the animal reports a percept involve
subsequent activation of many other areas of the cortex, especially frontal
regions. This suggests that for a visual stimulus to rise to the level of
conscious awareness, it must be <a href="https://pubmed.ncbi.nlm.nih.gov/21521609/">broadcast to the rest of the brain</a>.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The experiment with the crows was looking
for the same kind of marker or <b>neural correlate</b> of conscious perception. And
indeed they found it. Neurons in the posterior pallium of the crows (the nidopallium caudolaterale, for those keeping score at home) responded
in two ways: some neurons showed an immediate response to the visual stimulus
whether it was perceived or not. Others showed prolonged activity after the
stimulus was removed, which correlated much better with the subsequent
behavior of the animal than with the stimulus itself. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Importantly, because the crows don’t know
what they’re supposed to do with the information during this waiting period,
this neural activity should not be interpreted as merely preparation for a particular
motor action. Instead, the authors interpret it as reflecting a subjective
conscious signal that is maintained over this period. This interpretation is
supported by the fact that the patterns match the animal’s percept (as reported
by its behavior), <i style="mso-bidi-font-style: normal;">even when it was
mistaken</i>.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, what does all this tell us? The
similarity with the situation observed in primates prompts the authors to
conclude that crows are similarly having some kind of conscious experience. At
least, they take these data as evidence for “<a href="https://www.sciencedirect.com/science/article/abs/pii/S1364661304003183">access consciousness</a>”, meaning that
some internal neural state representing something in the outside world can be
maintained over time even in the absence of that stimulus and that this
information can be made available or broadcast to the rest of the brain and
subsequently acted upon.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">They are more cautious about taking it as
evidence for “<a href="https://www.sciencedirect.com/science/article/abs/pii/S1364661304003183">phenomenal consciousness</a>”, which would entail it <i style="mso-bidi-font-style: normal;">feeling like something</i> to have that
experience. Maybe it does, maybe it doesn’t – it’s not obvious at all that it
has to. And of course for animals without language, it’s almost impossible to
answer that question – if they can’t tell you that it feels like something,
it’s hard to find some other way to tell whether it does or not. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The question is whether it’s justified
calling this <i style="mso-bidi-font-style: normal;">consciousness</i> at all.
Maybe it’s just <a href="https://en.wikipedia.org/wiki/Working_memory">working memory</a> – maybe some neural circuits can maintain
reverberating patterns of activity over certain periods of time, can
communicate that activity to other parts of the brain, and can use it to inform
action. Does any of that have to entail subjective experience? I would guess
that lots of animals can probably do that kind of task, possibly even very simple ones (though readers may enlighten me otherwise). Indeed, it seems like you could
design circuits that would work like that in a robot without expecting it to
subjectively perceive anything. Could this all be achieved by mindless <a href="https://pubmed.ncbi.nlm.nih.gov/22210958/"><i style="mso-bidi-font-style: normal;">computation</i></a>?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Or maybe the alternative is true – maybe
that kind of internally sustained representation <i style="mso-bidi-font-style: normal;">defines</i> mental experience. Maybe you don’t need to add anything else
to that – maybe having such representations and being able to act upon them in
response to further information merits being called <i style="mso-bidi-font-style: normal;">cognition</i>. But does that necessarily entail subjective experience?
We can have cognition without consciousness so is there anything else here that
justifies the grand conclusion from this paper: that crows are conscious?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Well first there’s the question of what is
being represented. You might think it’s the visual stimulus but it isn’t just
that (it may not be that at all, after the initial brief moment) – it’s the <i style="mso-bidi-font-style: normal;">belief</i> of whether such a stimulus was
present or not. (Remember, the crow can be mistaken). The crow knows that it
will receive instructions to behave in one way or another depending on whether
it perceived the stimulus. It doesn’t have to maintain a trace of the visual
stimulus itself –which happens to be a grey square – just a record of its own
perceptual decision.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">As an aside, many people would quibble with
the word “representation” here, and for good reason. That term is used in so many
different and often only vaguely defined ways across neuroscience, cognitive
science, psychology, computer science, and philosophy. Here I think it is
justified, as it refers to a sustained pattern of activity that reflects a belief
about the world and that can be communicated or “re-presented” to other parts
of the brain to inform action.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This seems to go beyond a simple kind of
working memory in that what is being remembered or maintained is an inference,
not merely a stimulus. Does this thereby qualify as <i style="mso-bidi-font-style: normal;">mental</i> activity? Would it qualify as <i style="mso-bidi-font-style: normal;">comprehension</i>? Does the crow know what it knows? Or is it just
higher-order neural activity? Again, it seems like you could program that kind
of perceptual decision-making and retention of an abstracted signal of the
decision for some time in a robotic system, without entailing mentality.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The other characteristic relevant to
questions of consciousness is that this representation is made available to the
rest of the brain. This is reminiscent of the <a href="https://pubmed.ncbi.nlm.nih.gov/32135090/">Global Neuronal Workspace</a> theory of
conscious awareness developed by Stan Dehaene and colleagues. The idea is that
perceptual stimuli have to reach some threshold of neural activity in order to
ignite activity across a much wider network of the brain. In such cases the
stimulus is actually perceived consciously. When this ignition fails to occur
the stimulus is not perceived, though we can see that lower areas of visual
cortex respond the same in either case.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">(There is, incidentally, <a href="https://www.scientificamerican.com/article/the-neuroscience-of-tone/">congruent work</a> on
conditions like face blindness and tune deafness, which suggests that the
problem in these conditions is not the primary responsiveness of face or music
processing areas of the cortex, but rather the communication of signals from
these areas to frontal regions, necessary for conscious processing of those
stimuli).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">More broadly, in this hypothesis, percepts
are in some</span><span lang="EN-GB"></span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf1dyJXVitbKXdnC8I7BIg-1ejwd7o5SK9Sqqr-b60562jvC35nzNtfMHd1b97I9CaHgZexunlHDiAL77Ce_jMajse075cPHM6H0KCpYk9w2ycP9KWZsP6AZ4oRp598dsxBFB-1-FgGGyY/s1160/Screen+Shot+2020-09-30+at+8.27.58+AM.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="1054" data-original-width="1160" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf1dyJXVitbKXdnC8I7BIg-1ejwd7o5SK9Sqqr-b60562jvC35nzNtfMHd1b97I9CaHgZexunlHDiAL77Ce_jMajse075cPHM6H0KCpYk9w2ycP9KWZsP6AZ4oRp598dsxBFB-1-FgGGyY/s320/Screen+Shot+2020-09-30+at+8.27.58+AM.png" width="320" /></a></div><span lang="EN-GB"></span><span lang="EN-GB"> sense competing wit</span><span lang="EN-GB"></span><span lang="EN-GB">h each other for access to this global
workspace, this unified consciousness. It is in this global workspace that not
just percepts but also memories, ideas, beliefs, goals, plans, etc., are integrated, selectively attended to, and
acted upon to drive coherent and sophisticated behaviour. </span><p></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Is that the case in these crows? Who knows?
The experimental set up does not provide much scope for sophisticated behaviour
– they have been trained to respond in simple ways to this isolated
information, not to integrate it with other information and operate upon it in
any more complex way. However, the well-known problem-solving abilities of
crows (e.g., <a href="https://www.sciencedirect.com/science/article/pii/S0960982219300107">here</a>) suggest a highly developed capacity for reckoning and figuring of various
kinds.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">By themselves, the data in this paper can’t
really address the question of subjective conscious experience in these birds,
limited as they are to this very simple set up. But they’re certainly consistent
with some kind of mental life. Perhaps the ability to derive and maintain and
broadcast these kinds of perceptual beliefs (or other cognitive features that
can be abstracted away from direct current experience) is a necessary but not
sufficient function for mental experience. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Maybe that kind of activity would only
entail subjective experience in an organism with a broader sense of self,
phenomenologically calibrated through its own history of experience with a wider
world. It seems most likely that such capabilities exist in graded fashion
across the animal kingdom, not all-or-none. It’s probably an ill framed
question to ask: are crows conscious? Perhaps better to ask what their
consciousness is like.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><h1 class="article__headline"><div class="meta-line"><span style="font-size: small;">A neural correlate of sensory consciousness in a corvid bird</span><span style="font-size: small;"><span class="name">. <span style="font-weight: normal;">Andreas Nieder</span></span><span style="font-weight: normal;">, <span class="name">Lysann Wagener</span>, <span class="name">Paul Rinnert.</span><cite> Science </cite> 25 Sep 2020:</span></span><span style="font-weight: normal;"><span style="font-size: small;"> Vol. 369, Issue 6511, pp. 1626-1629<br />DOI: 10.1126/science.abb1447 </span></span> </div></h1>
<p><style>
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div.WordSection1
{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-70037289669001019192020-08-27T10:20:00.001-07:002020-09-11T05:12:23.382-07:00 Are bigger bits of brains better?<div class="separator"><div class="separator" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em; text-align: center;"><img border="0" data-original-height="1050" data-original-width="1280" height="256" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEguZ3L8jMB_tWE3Ti866zMYjOLy30inP7r172ujIclZxYJw4ezwLE5vriC1nDVd7WgyMahEh60i6I5RomzLZjSZTNA8RlIJQmJ8ytX4O1ck7Ja97bpw84KtEjRbV8XYsn32OCwXACIF9Kug/w313-h256/phrenology.png" title="(Pixabay)" width="313" /></div></div><p class="MsoNormal"><span lang="EN-GB"></span></p><p class="MsoNormal"><span lang="EN-GB">We scoff at the folly of <a href="https://en.wikipedia.org/wiki/Phrenology" target="_blank">phrenology</a> – the
simplistic idea that the size and shape of bumps on the skull could tell you
something about a person’s character and psychological attributes. It was all
the rage in the Victorian era (the early to mid-1800s) in the UK and the US
especially, with practitioners armed with calipers claiming to measure all
kinds of personal propensities, from Acquisitiveness and Combativeness to
Benevolence and Wonder. The skull bumps were just a proxy, of course – the idea
was that they reflected the size and shape of the underlying brain regions,
which were what was really associated with various traits. It all seems a bit
quaint and simplistic now (apart from the entrenched <a href="https://en.wikipedia.org/wiki/Phrenology#Racism" target="_blank">association with racism</a>),
but while we may like to think we have moved on, a lot of modern human
neuroscience is founded on the same premises. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">- The first premise is that different
mental functions or psychological traits can be localised to specific regions
of the brain. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">- The second is that the <i style="mso-bidi-font-style: normal;">size</i> of those regions is correlated with
the level of function or trait – usually with the idea that bigger is better. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">- And there is a third premise, which also
sometimes comes along for the ride, which is captured by the slogan “use it or
lose it” – the idea that if some brain area or function it supports is not
used, that brain area will get smaller; the converse idea is that if it is used
more, it will get bigger. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">These ideas are pervasive in the public perception
of neuroscience, promoted, in my view, by the way we neuroscientists tell our
stories. But this is not just a problem of communication of science – these
assumptions are also implicit and typically unexamined in the motivation for
and interpretation of many studies in the field. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">They weren’t plucked out of the air, of
course – there is some underlying truth to all of these ideas, and a relevant
evidence base supporting them. For example, lesion studies, patterns of brain
activation during various tasks, and the selective effects of stimulation of
various bits of the brain all support the partial localisation of all kinds of
cognitive functions. However, none of these kinds of evidence suggest that the
implicated brain regions carry out these functions by themselves. We now understand
that most cognitive functions are mediated by distributed networks, not by
isolated brain regions. There is certainly a high degree of specialisation of
function in that extended circuitry and it’s interesting and important to map
that out, but I think we’d all hope to have moved beyond naïve “blobology”. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Similarly, while there are plenty of
examples where size really does matter for some function or other, in both
animals and humans, it is not obvious that equivalences can be drawn across the
range of scenarios where this seems to hold. Differences in size and function (and
correlations between them) have been studied in many species across evolution,
across development, across the lifespan, across individuals, <a href="https://aeon.co/essays/the-gender-wars-will-end-only-with-a-synthesis-of-research" target="_blank">between sexes</a>,
across seasons, in pathological states, and in response to experience. Findings
from one of these areas are often used to bolster claims or motivate
experiments in another, but disparate underlying mechanisms may be at play
across these diverse scenarios.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">This is especially true in human studies as
the only non-invasive way to measure the size of bits of brains in humans is by
neuroimaging, which is extremely crude, relative to techniques that can be
applied to animal brains. Methods like <a href="https://en.wikipedia.org/wiki/Voxel-based_morphometry" target="_blank">voxel-based morphometry</a> (VBM) let you
gauge the size of different bits of the brain across individuals by warping 3D
images of their brains to a common template. You can similarly measure
thickness or surface area of bits of the cortex and compare across individuals.
But there are all kinds of different parameters at a cellular level that could
drive variation in the overall size of bits of the brain, which may be
indistinguishable by neuroimaging. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">These parameters include numbers of neurons,
numbers of astrocytes and oligodendrocytes, cell sizes, the extent of dendritic
or axonal arbors, numbers of synapses, myelination, vascularisation, or many
others. And each of those parameters is itself determined by multiple distinct
processes, such as proliferation, differentiation, migration, survival, growth,
pruning, and on and on. Very different processes and parameters will be at play
in different situations. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">To take a few examples, a difference in
size of some region over evolution may be caused by changes in proliferation
and neurogenesis, which could in turn have various underlying causes, such as
direct effects on cell cycle genes or indirect effects caused by differences in
afferent connectivity and the supply of growth factors; changes with aging may
track death of neurons or glial cells, loss of myelin or other degenerative
processes; while differences across individuals could be due to variation in neuronal
number or in things like the elaboration of neurites and synapses – the same
number of neurons, but with bushier connections. All of these may manifest as a
difference in size of some region by neuroimaging, but they’re not clearly meaningfully
related to each other. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">The causes of size differences are thus
quite diverse. What about the consequences? Is bigger necessarily better? There
certainly are cases where it is, but again, it’s important not to conflate
these or compare apples with oranges. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">When it comes to the whole brain, size
certainly matters. Brain size correlates well with intelligence <a href="https://www.pnas.org/content/109/Supplement_1/10661" target="_blank">across species</a>,
with bigger-brained species mostly being more intelligent, and especially a
consistent trend of increasing size in the primate lineage leading to humans. And
if we look across humans, <a href="https://pubmed.ncbi.nlm.nih.gov/26449760/" target="_blank">whole brain size also correlates with intelligence</a>
(measured in any of a variety of ways), with correlation coefficients in the
range of r=0.2–0.3. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span><span lang="EN-GB"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtnuHY5hAoB9C1DFcaF5XwBX74XcGg9-e6xKZ9PntWrap5sgKJb2mMwwjoos63EQo2s89AqQzZwN6YOiCtgNYwcPYkmXHOsZO-u6J5a8Jk3tXqzITAIIwD9q8os-jRRqP8s8e3ZLg9qsdX/s1280/brain+size+across+species.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="695" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtnuHY5hAoB9C1DFcaF5XwBX74XcGg9-e6xKZ9PntWrap5sgKJb2mMwwjoos63EQo2s89AqQzZwN6YOiCtgNYwcPYkmXHOsZO-u6J5a8Jk3tXqzITAIIwD9q8os-jRRqP8s8e3ZLg9qsdX/s640/brain+size+across+species.png" width="640" /></a></span></p><p class="MsoNormal"><span lang="EN-GB">There is an interesting exception to that,
however. Average male brain size in humans is about <a href="https://academic.oup.com/cercor/article/28/8/2959/4996558" target="_blank">10% larger</a> than average
female brain size, but there is <a href="https://journals.sagepub.com/doi/abs/10.1111/j.1745-6924.2008.00096.x" target="_blank">no difference in mean I.Q.</a> between the sexes.
This suggests <i style="mso-bidi-font-style: normal;">some other</i> sex
difference (in functional organisation, perhaps) counteracts the size effect on
I.Q., which otherwise holds within each sex. Even for the whole brain, size
clearly isn’t everything, a principle which holds <a href="https://www.frontiersin.org/articles/10.3389/fnana.2014.00015/full" target="_blank">true across species</a> too.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"><span lang="EN-GB">Whole brain size is also obviously the
grossest neuroanatomical measure you can get. What about smaller bits of the
brain? Does the size of any of them correlate with function or variation in
traits? If you’ve been reading the human neuroimaging literature for the last
couple of decades or the popular media describing it you would certainly be
convinced that many examples exist of such a relationship. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">I would guess there are thousands of published
papers reporting such an association. But I can’t think of any that have
robustly replicated and there is good evidence to suggest that most such
reports are spurious findings. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">A <a href="https://www.biorxiv.org/content/10.1101/2020.08.21.257758v1" target="_blank">very recent paper</a> by Marek and colleagues provides compelling
evidence that most such studies have been statistically <a href="https://www.nature.com/articles/nrn3475" target="_blank">underpowered</a> <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">by a
couple orders of magnitude</i></b>. Where sample sizes have typically been in
the tens or low hundreds, this paper shows that you need to get to samples in
the range of 10,000 people before you can detect robust associations between
neuroimaging measures and behavioural phenotypes. Below that, sample variance
leads to wildly fluctuating results, producing many false positive “findings” and
hugely inflated effect sizes. The pernicious effect of publication bias
massively exacerbates the problem in the literature. (The similarities to the
<a href="https://pubmed.ncbi.nlm.nih.gov/28386409/" target="_blank">candidate gene association literature</a> are not coincidental).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Moreover, even for the positive
associations that were found in this study, they were with extremely broad
psychological phenotypes – general cognitive ability and psychopathology – and
the anatomical measures associated with them were highly distributed across the
whole brain. What about more specific associations between the sizes of bits of
the brain and more specific traits or functions? Is there any reason to think
they should exist? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Clearly, we could reasonably expect that
the variation that we observe <a href="https://press.princeton.edu/books/hardcover/9780691173887/innate" target="_blank">in psychological traits</a> is caused by variation in
<i style="mso-bidi-font-style: normal;">some</i> parameters in the brain, but
should we expect them to be manifested at the macroscopic level probed by
neuroimaging? Or are we just taking that approach in humans because no other
methodology is available? Are we doing it just because it’s the only thing we
can do, not because there is a principled reason to expect such associations to
exist? </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">If the entirety of the prior literature
reporting such associations is now in question, is there any other evidence
base for the hypothesis that the size of specific brain regions is associated
with degree of function? Well, yes, though most of the evidence that springs to
my mind is somewhat indirect, for example from pathological situations, from
studies looking over evolutionary timescales, or from seasonal changes in some
animals that may be quite unusual.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In many neuropathological conditions, or
even in normal aging, the degree of loss of grey or white matter often
correlates with the severity of neurological or psychological symptoms.
However, as with lesion studies, there is a limit to how far this kind of
relationship can be extrapolated – greater loss of neural tissue in
pathological situations is certainly worse, but it’s not clear that having more
in a given area in a healthy situation (i.e., across individuals in the healthy
population) would necessarily be <i style="mso-bidi-font-style: normal;">better</i>
for some specific function.</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">In evolution, there are lots of examples of
differences in size of brain regions that correlate with behavioural
adaptations across species. For example, <a href="https://www.cell.com/trends/neurosciences/fulltext/S0166-2236(18)30209-1 " target="_blank">in mammals</a> that have evolved to use
various senses to different degrees, those senses that are used more have a
larger representation in the cerebral cortex. Different species may literally
need more neural real estate to effectively process the richer signals coming
in through the visual or auditory or olfactory domains. There’s no point having
bigger eyes with more photoreceptors of different kinds enabling more
sophisticated visual processing if the brain can’t handle that information. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p><p class="MsoNormal"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiFNJEXAvYDekv0SEOqk1vTmAVId7n_XAKSoBbCGRBA-fXCKVURSf7FE2FxK2mkDjxUfibnL9Cy4NU3uIdX7c5k-EAiicPSf_aifpKxRYulN3lLUBVb-XjJzzWSX1_PzAjeqejYuGYUpnjg/s1458/Screen+Shot+2020-08-27+at+6.16.37+PM.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1458" data-original-width="1242" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiFNJEXAvYDekv0SEOqk1vTmAVId7n_XAKSoBbCGRBA-fXCKVURSf7FE2FxK2mkDjxUfibnL9Cy4NU3uIdX7c5k-EAiicPSf_aifpKxRYulN3lLUBVb-XjJzzWSX1_PzAjeqejYuGYUpnjg/s640/Screen+Shot+2020-08-27+at+6.16.37+PM.png" /></a></div><span lang="EN-GB"> <br /></span><p></p>
<p class="MsoNormal"><span lang="EN-GB">It’s interesting to note that the
underlying mechanisms involve a dynamic communication between different parts
of the nervous system, from the sensory periphery through all the relays to the
higher perceptual centres. The size of any given brain region is not determined
solely by a genetic program that runs in isolation in those cells – it is also
affected by proliferation signals and neurotrophic factors released by incoming
nerve fibres from other regions in the circuit. Thus, over both development in
individuals and the evolution of species, the size of functionally coupled regions
is tightly coordinated. (Indeed, cortical thickness within individuals is
<a href="https://pubmed.ncbi.nlm.nih.gov/23531697/" target="_blank">correlated</a> between regions that make up extended functional circuits).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">An even more dynamic relationship between
size and function is observed in some animals with seasonal changes in the size
of some brain region. For example, in <a href="https://pubmed.ncbi.nlm.nih.gov/26032719/" target="_blank">some male songbirds</a>, the high vocal
centre or “song nucleus” grows in response to changes in day length and
hormonal signals, giving them more neural resources for the mating season, when
their singing needs to be on point. Similarly, some mammals and birds show
changes in the <a href="https://www.semanticscholar.org/paper/Seasonal-changes-in-hippocampus-size-and-spatial-in-Yaskin/1d8f878e4ffd3638cbd913db94deb922f27406a9" target="_blank">size of the hippocampus</a> across seasons, which may reflect
different behavioural demands on navigational abilities across the seasons. Such
changes involve high levels of neural turnover and proliferation of new
neurons, tightly regulated by a variety of signaling mechanisms. </span></p><br /><p class="MsoNormal"><span lang="EN-GB">These seasonal changes thus represent good
examples of all three premises: particular behavioural functions in these
species do rely (especially though not exclusively) on these specific brain
areas; the size of these areas does seem to reflect degree of functional
capability; and when they are not needed at full capacity they shrink
(presumably due to an otherwise unnecessarily high metabolic cost of maintaining
them). </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Though humans don’t show such seasonal
changes, there are numerous reports of differences in brain region size that
are supposedly driven by differences in experience and associated with the
level of some cognitive function. The most famous of these reports involve
<a href="https://www.pnas.org/content/97/8/4398" target="_blank">London taxi drivers</a>, who were found to have larger hippocampi (specifically the
posterior portion) than non-taxi-driving subjects. The interpretation was that
this difference was driven by their intense training on the geography of London
streets (“the knowledge”), with the implication at least that this increase in
size improved their navigational abilities. </span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">[Note added: See also a <a href="https://www.sciencedirect.com/science/article/pii/S096098221101267X" target="_blank">subsequent paper</a> finding a change in hippocampal size following training: </span><span lang="EN-GB">
</span></p><p class="MsoNormal"><span lang="EN-GB">Acquiring “the Knowledge” of London's
Layout Drives Structural Brain Changes]</span></p><p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"><style>
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<p class="MsoNormal"><span lang="EN-GB">These studies are very well known and
effectively taken as lore, both in the field and by the general public. (I have
had taxi drivers themselves tell me about these findings). Without dwelling on
it, I think the design of the original studies would not stand up well to
current expectations, especially in terms of sample sizes, which were in the
tens (not the tens of thousands). Moreover, <a href="https://pubmed.ncbi.nlm.nih.gov/32739555/" target="_blank">larger studies </a>have not observed a
relationship in the general population between size of the hippocampus (or bits
of it) and navigational abilities.<span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Again, the rationale for the hypothesis
that bits of the brain should grow with use is rather vague. Are we expecting
new neurons to be produced? (This might be the case in the hippocampus though
even there the question of whether <a href="https://pubmed.ncbi.nlm.nih.gov/32848586/" target="_blank">adult neurogenesis</a> actually occurs in humans
is controversial). Or would it be driven by growth of dendrites and synapses?
Or maybe very active regions get swole by attracting a bigger supply of blood
vessels?</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">But what does “very active” even mean here?
This idea harkens back to the myth that we only use 10% of our brains. Really
we’re using all of our brains, all the time, and even when we’re not obviously
actively “doing something” with some brain region, there’s still loads of
background neural activity there. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Are the hippocampi of taxi drivers really <i style="mso-bidi-font-style: normal;">more</i> active than those of other folks? I
don’t just mean that they are using them more to navigate – I mean that if you
measured the actual neural activity in those structures over some period of
time, it would be on average higher (to an extent that might plausibly drive a
cellular physiological response and growth of the whole area). That might be
true but I don’t think it’s been shown. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Or are they in some way <i style="mso-bidi-font-style: normal;">differently</i> active? Maybe there’s more
high-frequency firing or more synchronised firing or variation in some other
global parameter without a change in overall number of spikes. Perhaps cells
could monitor and respond to such parameters. There is an extensive body of
literature in animals showing that both levels and patterns of neural activity
do <a href="https://pubmed.ncbi.nlm.nih.gov/30359600/" target="_blank">feed back onto gene expression</a> in ways that are important for both
activity-dependent development and plasticity. As far as I know, however, these
have not been linked to macroscopic growth of whole areas but rather to highly
cell-type-specific microscopic changes in connectivity. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">More generally, it is true that <a href="https://www.nature.com/articles/1301559" target="_blank">synaptic plasticity</a> and learning, especially the formation of long-term memories,
involves the <i style="mso-bidi-font-style: normal;">physical growth</i> of new
synaptic connections. However, this is not one-way: synaptic plasticity equally
involves the weakening and pruning of connections under other conditions.
Moreover, absolute increases in overall numbers or strength of synapses are
actively counteracted by <a href="https://pubmed.ncbi.nlm.nih.gov/28093556/" target="_blank">homeostatic processes</a> that reduce overall synaptic
connectivity (especially during sleep), maintaining relative changes in
strength, while renormalizing the responsiveness of the network to new
experience. </span></p><br /><p class="MsoNormal"><span lang="EN-GB">In short, brain is not like muscle. Bits of
brain don’t just grow with experience – they mainly change by reorganising
their internal connectivity. This is just as well because if the brain did
continue to grow with use, all of our brains would be busting out of our
skulls. I don’t mean to be too sarcastic (just the right amount), but I’ve been
going around seeing things like crazy – really intensely using my visual system
for many years now – without causing massive growth of my visual cortex. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">So, where does all this leave us? Let’s
reconsider our three premises:</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Can we localise functions to specific brain
areas? We can certainly implicate areas as being involved more in or required
more for some functions than others, without falling into the trap of thinking
that they are somehow sufficient for those functions. (You can say the same for
genes).</span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Is bigger better? In many scenarios –
evolutionary, developmental, pathological – the answer is clearly yes. I’m sure
that readers will think of many other examples that fit with this general idea.
But to return to where we started, with phrenology, those observations do not
necessarily imply that variation in size of bits of brain should contribute to variation
across the normal range of behavioural traits or cognitive functions within
humans. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Should we expect variation in extraversion
or impulsivity or <a href="http://www.wiringthebrain.com/2019/07/the-murderous-brain-can-neuroimaging.html" target="_blank">murderousness</a> or spatial reasoning or working memory or
creativity be associated with the <i style="mso-bidi-font-style: normal;">macroscopic
size</i> of specific brain regions, as measurable by neuroimaging? Maybe. It’s
not an entirely daft idea, it’s just really crude and simplistic, in my
opinion. An alternative hypothesis that I find more likely is that variation in
those kinds of complex psychological traits and cognitive functions will be due
to idiosyncratic combinations of distributed and likely subtle effects on all
kinds of cellular and biochemical parameters affecting the function and computational
operations of highly extended circuitry across the brain. Complex traits are
called that for a reason. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">And finally, do bits of brain grow with use
in a way that mediates greater function? The motivation for this hypothesis is vague
and weak, in my opinion, and though it is taken as lore, the evidence for this
kind of effect in humans is on far shakier ground than many people both in the
field and in the general public appreciate. <span style="mso-spacerun: yes;"> </span></span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">Generally speaking, while our technology
has improved, we won’t make progress in understanding the complex relationships
between human brain structure and function and our individual psychological
traits armed only with Victorian-era theories. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
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div.WordSection1
{page:WordSection1;}</style></p>Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-37901215118256582602020-07-31T03:42:00.001-07:002020-07-31T03:42:12.725-07:00Escaping Flatland - when determinism falls, it takes reductionism with it<div dir="ltr" style="text-align: left;" trbidi="on">
<br />
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">For the reductionist, reality is flat. It
may seem to comprise things in some kind of hierarchy of levels – atoms,
molecules, cells, organs, organisms, populations, societies, economies,
nations, worlds – but actually everything that happens at all those levels
really derives from the interactions at the bottom. If you could calculate the
outcome of all the low-level interactions in any system, you could predict its
behaviour perfectly <i>and there would be
nothing left to explain</i>. It’s turtles all the way down. <div class="separator" style="clear: both; text-align: center;">
</div>
</span>
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB"><a href="https://en.wikipedia.org/wiki/Reductionism">Reductionism</a> is related to determinism,
though not in a straightforward way. There are different <a href="https://plato.stanford.edu/entries/determinism-causal/">types of determinism</a>, which
are intertwined with reductionism to varying degrees.</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">The reductive version of determinism claims
that everything derives from the lowest level AND those interactions are
completely deterministic with no randomness. There are things that <i>seem</i> random, to us, but that is only a
statement about our ignorance, not about the events themselves. The randomness
in this scenario is epistemological (relating to our knowledge or lack of it),
not ontological (a real thing in the world, that we can observe, but that does
not depend on us for its existence). </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">That’s the clockwork universe – the one
where <a href="https://en.wikipedia.org/wiki/Laplace%27s_demon">Laplace’s Demon</a> (an omniscient being) could unerringly predict the future
of the entire universe from a fully detailed snapshot of the state of all the
particles in it at any given instant. It’s pretty boring, that kind of
universe. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">There is also an ostensibly non-reductive flavour
of determinism, which simply affirms that every event has some antecedent physical
cause(s). Nothing “just happens”. Under this view, however, causes don’t have
to be located solely in the interactions of all the particles or limited to the
actions of basic physical forces (which also act at the macroscopic scale,
determining the orbits of the planets, for example). The causality, or some of
it at least, could inhere in the organisation of a system and the constraints
that it places on the interactions of its constituents. In this kind of scheme,
there is room for a why as well as a how.</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">That’s the argument, at least, though it’s
a little incoherent, in my view. If there is no real randomness in the system
(or in the universe as a whole), then I don’t see how you can escape from pure
reductionism. In a deterministic system, whatever its current organisation (or
“initial conditions” at time <i>t</i>) you
solve Newton’s equations or the Schrodinger equation or compute the wave
function or whatever physicists do (which is in fact <i>what the system is doing</i>) and that gives the next state of the
system. There’s no why involved. It doesn’t matter what any of the states mean
or why they are that way – in fact, there can never be a why because the
functionality of the system’s behaviour can never have any influence on
anything. I would go even further and say you can never get a system that <i>does things</i> under strict determinism.
(Things would happen in it or to it or near it, but you wouldn’t identify the
system itself as the cause of any of those things).</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">But what if determinism is false? Let’s see
what happens to reductionism when you introduce some randomness, some
indeterminacy in the system. Of course, this is exactly what <a href="https://en.wikipedia.org/wiki/Quantum_mechanics">quantum theory</a>
does, at least under one interpretation, though there is deep disagreement
among physicists as to whether the randomness observed at quantum levels is
epistemological or ontological. But let’s say it’s the latter – that randomness
really exists in the universe – that some things, at very small scales at
least, do “just happen”.</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">What effect does that have on things at big
scales – the scales of rocks and cats and babies, and other things we care
about? Some people argue – rather casually, in my view – that randomness at
quantum levels will not have any effect at the level of classical physics,
because all that noise will be somehow absorbed or averaged out in the system
and will not percolate up to higher levels. This means the behaviour of the
system at classical levels can still be considered to be deterministic. <span> </span></span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">Is that true? Do quantum effects stay there
at the quantum level? I can think of lots of instances where they wouldn’t –
like <a href="https://en.wikipedia.org/wiki/Schr%C3%B6dinger%27s_cat">Schrödinger’s famous cat</a>, for example, whose fate was to be determined by
the random decay of a radioactive atom. And I would guess that the randomness
of quantum phenomena has some important implications for real-world quantum
computing.<span> </span></span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">But just speaking philosophically, what’s strange
about this assertion – as I said, often thrown out very casually – is that it betrays
the very idea of reductionism. It relies on the idea that reality is not in
fact flat. It claims explicitly that things can be happening at the lowest
level of the system that do not percolate up to higher levels. Heresy! How can
a good reductionist believe that? Does reductionism only apply at classical
levels? Does it stop being true at some scale? Why?</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">If the properties at the classical level
derive from interactions at the quantum level (and we know they do because they
can be derived from quantum theory), then why would the subset of such
interactions that happen to have arisen randomly not also manifest at higher
levels? How would the system know which ones were random and which were
determined? </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">I know that’s a silly way to put it, but it
highlights something crucial – the idea that something important is happening <i>at the level of</i> <i>the system</i>. You might say that the reason those quantum
fluctuations don’t manifest at the level of the whole system is because they
average out. They are random, after all, and if there are many of them and they
are independent, then their collective effects should cancel each other out.
But that relies on a very non-reductionist mechanism: coarse-graining. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">For that averaging out to happen, it means
that the low-level details of every particle in a system are not all-important
– what is important is the average of all their states. That describes an
inherently <i>statistical</i> mechanism. It
is, of course, the basis of the laws of thermodynamics and explains the
statistical basis of macroscopic properties, like temperature. But its use here
implies something deeper. It’s not just a convenient mechanism that we can use
– it implies that <i>that’s what the system
is doing</i>, from one level to the next. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">Once you admit that, you’ve left Flatland.
You’re allowing, first, that levels of reality exist. And second, that what
happens at one level is only a coarse-grained, statistical reflection of what
is happening at the level below. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">In my view, that’s almost but not quite right.
Any hierarchical system is averaging, or integrating over, or in some way
coarse-graining the low-level details, but not just the random ones (how could
it be?) – it’s coarse-graining ALL of them. And not just from the lowest,
quantum level, to the next one up. This happens at EVERY level. It may be
turtles all the way down, but it’s not turtles all the way up.</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">The macroscopic state as a whole does
depend on some particular microstate, of course, but there may be a set of such
microstates that corresponds to the same macrostate. And a different set of
microstates that corresponds to a different macrostate. If the evolution of the
system depends on those coarse-grained macrostates (rather than on the precise
details at the lower level), then this raises something truly interesting – the
idea that <i><a href="https://plato.stanford.edu/entries/information/">information</a> </i>can have causal
power in a hierarchical system, and, more generally, in the universe. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">The low level details alone are not
sufficient to predict the next state of the system. Because of random events,
many next states are possible. What determines the next state (in the types of
complex, hierarchical systems we’re interested in) is what macrostate the
particular microstate corresponds to. The system does not just evolve from its
current state by solving classical or quantum equations over all its
constituent particles. It evolves based on whether the current arrangement of
those particles corresponds to macrostate A or macrostate B. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">Some criteria embodied in the structure of
the system itself drive a different response to these two macrostates. Simple
versions could involve a threshold effect, such as a thermostat triggering a
heater if the temperature drops below its set point, or a neuron firing an
action potential if the voltage across its membrane is high enough. That kind
of control is inherently <i>informational</i>.
In philosophical terms, it relies on <a href="https://plato.stanford.edu/entries/counterfactuals/">counterfactuals</a> being <i>ontologically</i> real – that is, the current state can only carry
causally effective information if in fact it was actually possible that it
could have been different. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">That little bit of indeterminacy is thus key
– otherwise it doesn’t matter what the microstate corresponds to as the system
is simply going to follow a deterministic trajectory. But I’ve just been talking
about those random events being coarse-grained, along with all the non-random
events, so how could they lead to different macrostates? The answer is they’re
averaged but not always <i>averaged out</i>.
Sometimes those random events will make a crucial difference, especially for a
system poised at the boundary between two macrostates. In fact, such a scenario
actually <i>amplifies</i> small random
fluctuations, by causing a qualitative change in macrostate. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">In complex, dynamical systems that are far
from equilibrium, some small differences due to random fluctuations may thus indeed
percolate up to the macroscopic level, creating multiple trajectories along
which <i>the system could evolve</i>. This
brings into existence something necessary (but not by itself sufficient) for things
like agency and free will: <i>possibilities</i>.
</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<br /></div>
<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">What this means is that causation does not
reside simply at the lowest levels and the basic laws of physics, nor is it
completely instantaneous. The system will not evolve along a single
pre-determined line, nor will its evolution simply follow a random path in a
tree of possibilities. Instead, in some types of systems – like living
organisms – how the system evolves will depend on what those various
macrostates <i>mean</i>. What do they
correspond to or reflect in the environment, what consequences are they linked
to in terms of action, what feedback does the organism get on the outcomes of
those actions, and how does that feedback alter the configuration of the system
to set criteria for processing that information in the future? </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">By building up, not out, creating a
functional hierarchy of levels within their own structure, and incorporating
meaning in feedback loops that extend through action and consequence into the
environment and over time, evolution has created organisms that use the wiggle
room provided by stochasticity to exert “top-down” causal power to do things
for reasons. The organism itself can <i>choose</i>
among those branching possibilities. (More on that <a href="https://pubmed.ncbi.nlm.nih.gov/29961596/">here</a> and much more to come).</span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
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<span style="font-size: small;"><span style="font-family: inherit;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">To come back to where we started, while
they are often presented as independent, I argue that if strict
determinism falls, it takes reductionism down with it. Turns out a little bit
of randomness is the key to escaping Flatland. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: inherit;">
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<span style="font-size: small;"><span style="font-family: inherit;"><b><span lang="EN-GB">Further reading:</span></b></span></span></div>
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<br /></div>
<div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB">Mitchell KJ. <a href="https://pubmed.ncbi.nlm.nih.gov/29961596/">Does Neuroscience Leave Room for Free Will?</a>. <i>Trends Neurosci</i>. 2018;41(9):573-576. doi:10.1016/j.tins.2018.05.008 </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: inherit;"><span lang="EN-GB"></span><span style="font-weight: normal;">Sara Imari Walker (2014) <a href="https://www.mdpi.com/2078-2489/5/3/424">Top-down causation and the rise of information in the emergence of life</a>.<em> Information</em> 2014, <em>5</em>(3), 424-439; <a href="https://doi.org/10.3390/info5030424">doi:10.3390/info5030424</a>
</span></span></span></div>
<div class="highwire-citation-info">
<div class="highwire-article-citation highwire-citation-type-highwire-article" data-apath="/pnas/110/49/19790.atom" data-node-nid="160037" data-pisa-master="pnas;1314922110" data-pisa="pnas;110/49/19790" id="node160037--2">
<div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-standard clearfix">
<span style="font-size: small;"><span style="font-family: inherit;"><br /></span></span>
<div class="highwire-cite-authors">
<span style="font-size: small;"><span style="font-family: inherit;"><span class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">Erik P.</span> <span class="nlm-surname">Hoel</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Larissa</span> <span class="nlm-surname">Albantakis</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Giulio</span> <span class="nlm-surname">Tononi</span></span></span>. <a href="https://www.pnas.org/content/110/49/19790.short">Quantifying causal emergence</a>.</span></span></div>
<div class="highwire-cite-metadata">
<span style="font-size: small;"><span style="font-family: inherit;"><span class="highwire-cite-metadata-journal highwire-cite-metadata">PNAS </span><span class="highwire-cite-metadata-date highwire-cite-metadata">Dec 2013, </span><span class="highwire-cite-metadata-volume highwire-cite-metadata">110 </span><span class="highwire-cite-metadata-issue highwire-cite-metadata">(49) </span><span class="highwire-cite-metadata-pages highwire-cite-metadata">19790-19795; </span><span class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.1073/pnas.1314922110 </span></span></span></div>
</div>
</div>
</div>
<h1>
<span style="font-size: small;"><span style="font-family: inherit;"><span style="font-weight: normal;">Krakauer D, Bertschinger N, Olbrich E, Flack JC, Ay N. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244620/">The information theory of individuality</a>. <i>Theory Biosci</i>. 2020;139(2):209-223. doi:10.1007/s12064-020-00313-7<span lang="EN-GB"></span></span></span></span></h1>
<div class="citation-text" data-citation-style="ama">
<span style="font-size: small;"><span style="font-family: inherit;">Noble R, Noble D. <a href="https://pubmed.ncbi.nlm.nih.gov/30384641/">Harnessing stochasticity: How do organisms make choices?</a>. <i>Chaos</i>. 2018;28(10):106309. doi:10.1063/1.5039668</span></span></div>
<div class="citation-text" data-citation-style="ama">
<span style="font-size: small;"><span style="font-family: inherit;"> </span></span></div>
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Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-75484481380272928012020-01-04T06:47:00.001-08:002020-01-04T06:47:44.977-08:00How much innate knowledge can the genome encode?<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgEKGb1hC6NirB-z_eRJXCetGKfT5TqKtyBQTSMFzwYFLoDq8pJN67x0EGrQwSGdOY0EaYmxtJYuzEOGXZPUqZ5v-fqbUE5UJbBl5LkUhJ7iCrmhJfLgMj37TNBDFSjaLIwIyQbWbLcGvle/s1600/dna-brains-2.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="610" data-original-width="781" height="249" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgEKGb1hC6NirB-z_eRJXCetGKfT5TqKtyBQTSMFzwYFLoDq8pJN67x0EGrQwSGdOY0EaYmxtJYuzEOGXZPUqZ5v-fqbUE5UJbBl5LkUhJ7iCrmhJfLgMj37TNBDFSjaLIwIyQbWbLcGvle/s320/dna-brains-2.jpg" width="320" /></a><span lang="EN-GB">In a <a href="https://www.youtube.com/watch?v=EeqwFjqFvJA">recent debate</a> between Gary Marcus and
Yoshua Bengio about the future of Artificial Intelligence, the question came up
of how much information the genome can encode. This relates to the idea of how
much innate or prior “knowledge” human beings are really born with, versus what
we learn through experience. This is a hot topic in AI these days as people
debate how much prior knowledge needs to be pre-wired into AI systems, in order
to get them to achieve something more akin to natural intelligence. </span></span></span><br />
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Bengio (like Yann leCun) argues for putting
as little prior knowledge into the system as we can get away with – mainly in
the form of meta-learning rules, rather than specific details about specific
things in the environment – such that the system that emerges through deep
learning from the data supplied to it will be maximally capable of generalisation.
(In his view, more detailed priors give a more specialised, but a more limited and
possibly more biased machine). Marcus argues for more prior knowledge as a
scaffold on which to efficiently build new learning. He points out that this is
exactly how evolution has worked – packing that kind of knowledge into the
genomes of different species.</span></span></span>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Of course, the question is how that works.
How does information in the genome lead to pre-wiring of the nervous system in
a way that automatically connects external stimuli to internal values or
associations? </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">In the course of a brief discussion on this
point, Bengio argued that there is not, in fact, enough information in the
genome to encode much prior knowledge:</span></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><i><span lang="EN-GB"> “…there’s
lots of room in the genome but clearly not enough to encode the details of what
your brain is doing. So, it has to be that learning is explaining the vast
majority of the actual computation done in the brain, just by counting
arguments: twenty thousand-odd genes, with a hundred billion neurons and a
thousand times more connections”. </span></i></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Marcus responded with a reference to his excellent
book “<a href="https://www.amazon.co.uk/Birth-Mind-Creates-Complexities-Thought/dp/0465044069">The Birth of the Mind</a>”, in which he refutes this “genome shortage
argument”, which he suggests people take as implying that most of our knowledge
is learned and that there simply isn’t enough information in the genome to
specify a lot of priors. </span></span></span></div>
<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB"> </span></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"></span></span><div class="MsoNormal">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Unfortunately, their discussion veered off
this topic pretty quickly, but it’s a very interesting question and, in my
view, the way that Bengio phrased it – as a simple numerical argument –
completely misconceives the way in which the kind of information we are after
is encoded in the genome. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">He is not alone. This discussion harks back
to <a href="https://science.sciencemag.org/content/309/5731/80">an issue</a> that exercised many people in the biological community when the
Human Genome Project completed the first draft of the human genome and it turned
out that we had far fewer genes than had previously been thought. Previous
estimates had put humans at about 100,000 genes (each one coding for a
different protein), based on extrapolation from a variety of kinds of data, the
details of which are not really important. When it turned out we have only
about 20,000 genes, there were gasps of horror, as this number was not even
twice as many as lowly fruitflies or even vastly simpler nematodes, which each
have ~15,000 genes. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Nematodes only have ~1,000 cells, ffs! If
we are so complex (and we are, if nothing else, stubbornly impressed with
ourselves), how can we have only on the same order of genes as a crappy little
worm that doesn’t even have a brain? And, as Bengio and others argue, if we
have only this limited number of genes, how can we encode any kind of
sophisticated priors in the connectivity of our brains, which is mathematically-speaking
vastly more complicated? </span></span></span></div>
<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
</span></span><div class="MsoNormal">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><b><span lang="EN-GB">Counting
the wrong things</span></b></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">To me, this kind of thinking misconceives
entirely the way that developmental information is encoded in the genome. It’s
not the number of genes that matters, it’s the way that you use them. From a
developmental perspective, the number of proteins encoded is not the measure of
complexity. The human genome encodes almost exactly the same set of proteins as
every other mammal, with few meaningful differences in the actual amino acid
sequences. In fact, the biochemical sequence and functions of most proteins are
in many cases conserved over much larger evolutionary distances – from insects to
mammals, for example. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">As one famous experiment illustrates (and
many others have found) it is often possible to substitute a fly version of a
protein with the mouse version and have it function perfectly normally. <a href="https://www.ncbi.nlm.nih.gov/pubmed/9078363">The experiment</a> I’m thinking of was looking at a gene called <i>eyeless</i> in flies (because mutant flies lacking the gene have no
eyes) and <i>Pax6</i> in mice. <i>Eyeless/Pax6</i> is known as a “master
regulator” gene – it encodes a transcription factor that regulates a cascade of
other genes necessary for eye development, in both flies and mice.
</span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB"><br /></span></span></span></div>
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</span></span><div class="MsoNormal">
<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">If you drive expression of the Eyeless
protein in parts of the developing fly that give rise to other appendages like
antennae, legs, or wings, you can convert those appendages into eyes as well.
Amazingly, if you express the mouse version, Pax6, in these tissues, the same
thing happens – you form extra ectopic eyes (fly eyes, not mouse eyes). So, the
differences in amino acid sequence between the proteins encoded by <i>eyeless</i> and <i>Pax6</i> don’t make much of a difference to its function. What does
make a difference is the context in which it is expressed – the network of
genes that the protein regulates in each species and the subsequent cascading
developmental trajectory. </span></span></span></div>
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiSuffZbTnvAMYBc2mfKCKNi3WCK_A8nrLBd6YCxNqDuIqCF7fCE_XXqD3-NLrB5A0NZxgWMXVBronIt4ZGA9jnIvkPvrFWH04CodvaUgxUzMf0XDZOehoZYUqDomDxP2a47czv56BRag7u/s1600/Screen+Shot+2020-01-04+at+2.21.14+PM.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="772" data-original-width="1286" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiSuffZbTnvAMYBc2mfKCKNi3WCK_A8nrLBd6YCxNqDuIqCF7fCE_XXqD3-NLrB5A0NZxgWMXVBronIt4ZGA9jnIvkPvrFWH04CodvaUgxUzMf0XDZOehoZYUqDomDxP2a47czv56BRag7u/s400/Screen+Shot+2020-01-04+at+2.21.14+PM.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Expression of eyeless in other tissues <a href="https://science.sciencemag.org/content/267/5205/1788.long">drives formation</a> of ectopic eyes</td></tr>
</tbody></table>
<div class="separator" style="clear: both; text-align: center;">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">This relies not on the protein-coding
sequences, but on the so-called regulatory sequences of the target genes. These
are short stretches of DNA, often adjacent to the protein-coding bits, which
act as binding sites for other proteins (<a href="https://en.wikipedia.org/wiki/Transcription_factor">transcription factors</a> or <a href="https://en.wikipedia.org/wiki/Chromatin_remodeling">chromatin regulators</a>), which control when and where a protein is expressed – in which
cell types and at what levels. </span></span></span></div>
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</span></span><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjPHe2PvZWjNhrjTvxI4OuAnMb4KuOURpBzXJ8mA_I5yY_i8UYw955oWEK0wxjNIVr93OUDet3ytN0MZjv3n3vhm2fqXclNU3PzCvJmpSUPlEHsNlVs5iElg8KP2uhEf7EHW0lNi7lX6CSt/s1600/03-01_mitchell_fig_FINAL3.27+copy.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1600" data-original-width="1223" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjPHe2PvZWjNhrjTvxI4OuAnMb4KuOURpBzXJ8mA_I5yY_i8UYw955oWEK0wxjNIVr93OUDet3ytN0MZjv3n3vhm2fqXclNU3PzCvJmpSUPlEHsNlVs5iElg8KP2uhEf7EHW0lNi7lX6CSt/s640/03-01_mitchell_fig_FINAL3.27+copy.jpg" width="488" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">From <a href="https://press.princeton.edu/books/hardcover/9780691173887/innate">Innate</a></td></tr>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">These <a href="https://www.ncbi.nlm.nih.gov/pubmed/29759817">regulatory elements</a> typically work in
a modular fashion and are much <a href="https://www.ncbi.nlm.nih.gov/pubmed/27863239">more evolvable</a> than the sequences of the
regulatory proteins. The latter are highly functionally constrained because
each such protein regulates many targets and any change in its sequence will
have many, diverse effects. (This is probably why they work the same even
across distantly related species). By contrast, changing the binding site for
one protein that regulates gene A will change only that aspect of the
expression pattern of gene A which that protein regulates, leaving all other
aspects and all other genes unchanged. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">The complexity of those regulatory sequences
is not at all captured by the number of genes. Indeed, it is not even captured
by the number of such elements themselves, as they interact in combinatorial
and highly context-dependent ways, in cooperation or competition with different
sets of factors in different cell types and at different stages of development.
(For example, Pax6 in mammals is also involved in <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=12878679">patterning the developing neocortex</a> and in specifying a number of <a href="https://www.ncbi.nlm.nih.gov/pubmed/9230312">different cell types</a> in the developing
spinal cord, in combination with other transcription factors). The complexity
of the output thus should not be expected to scale linearly with the number of
genetic elements. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Being amazed that you can make a human with
only 20,000 genes is thus like being amazed that Shakespeare could write all
those plays with only 26 letters. It’s totally missing where the actual,
meaningful information is and how it is decoded. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><b><span lang="EN-GB">How
do we measure information?</span></b></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Part of the problem is in thinking of
<a href="https://en.wikipedia.org/wiki/Information_theory">Shannon information</a> as the only measure of information content that is really
scientific (nicely described in James Gleick’s “<a href="https://www.penguinrandomhouse.com/books/60765/the-information-by-james-gleick/">The Information</a>”). Shannon information
(named after Claude Shannon) simply relates to the efficiency of encoding
information for signal transmission. It is measured in bits, which correspond
to how many “yes or no” questions you would have to ask to derive the original
message that you want to transmit. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Importantly, this does not take into
account at all <b><i>what the message means</i></b>. Indeed, a purely random sequence of
letters has greater Shannon information than a string of words that make up a
sentence, because the words and the sentence have some higher-order patterns in
them (like statistics of letters that typically follow each other, such as a
“u” following a “q”), which can be used to compress the message. A random
sequence has no such patterns and thus cannot be compressed. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Thinking in those terms naturally leads to
the kind of “counting arguments” that Bengio makes. These seem to take each
gene as a bit of information, and ask whether there are enough such bits to
specify all the bits in the brain, usually taken as the number of connections. Obviously
the answer is there are not enough such bits. (There aren’t even enough bits if
you take individual bases of the genome as your units of information). </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">But the genome is not a blueprint. Bits of
the genome do not correspond to bits of the body (or bits of the brain). The
genome is much more like a program or an algorithm. And computer scientists
have a much better measure to get at how complex that program is, which is
known as algorithmic complexity (or <a href="https://en.wikipedia.org/wiki/Kolmogorov_complexity">Kolmogorov complexity</a>). This is the length
of the shortest computer program that can produce the output in question. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><b><span lang="EN-GB">How
complex is your code?</span></b></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">What we really would like to know is the
Kolmogorov complexity of the human brain – how complex does the developmental
program have to be to produce it? (More specifically, to get it to
self-assemble, given the right starting conditions in a fertilised egg). And,
most germane for this discussion, how complex would that program have to be to
specify lots of innate priors? </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Speaking as a developmental neurobiologist,
if we knew the answers to those questions, we’d be done. We can’t figure out or
quantify how complex the developmental program is until we know what the
developmental program is (*but see note from Tony Zador, below). In fairness, <a href="https://www.jneurosci.org/content/29/41/12735">we know a lot</a> – the field is in some ways quite mature, at least in terms of major
principles by which the brain self-assembles based on genomic instructions. But
I think it’s also fair to say that we do not have a complete understanding of
the molecular logic underlying the guidance of the projections and the
formation of synaptic connections of even a single neuron (like <a href="https://dev.biologists.org/content/119/Supplement/227">this one</a>, for
example) in any species. What we can say is that that logic is highly
<a href="https://www.ncbi.nlm.nih.gov/pubmed/9604933">combinatorial</a>, meaning you can get a lot of complexity out of a limited set of
molecules. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">And we are only beginning to understand how
instinct and innate preferences and behaviors are <a href="https://www.frontiersin.org/articles/10.3389/fnmol.2012.00055/full">wired into the circuitry of the brain</a>. There are growing numbers of examples of subtle genetic differences
that lead to specific differences in neural circuitry that explain differences
in behaviour. Some of these relate to differences in behaviour between closely
related species (such as <a href="https://www.ncbi.nlm.nih.gov/pubmed/16255009">monogamy vs polygamy</a>, or geometry of <a href="https://www.ncbi.nlm.nih.gov/pubmed/27496333">tunnel building</a>).
But probably the best-studied are sex differences within species, where a
subtle genetic difference between males and females (the activity of the Sxl
gene <a href="https://www.ncbi.nlm.nih.gov/pubmed/26851712">in flies</a> or the presence of the SRY gene <a href="https://www.ncbi.nlm.nih.gov/pubmed/20970320">in mammals</a>, for example) shifts
the developmental trajectory of certain circuits, and pre-wires preferences and
behaviours.</span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">It’s an exciting time for this kind of
research, with lots of amazing new tools being focused on fascinating
biological questions in all kinds of species, but really this work is only just
beginning. Moreover, it typically focuses on how a <i>difference</i> in the genome leads to a <i>difference</i> in circuitry and innate behaviour. It doesn’t explain
the full program required to specify all of the circuitry on which any such
behaviour is built. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">So, we simply can’t currently answer the
question of how complex the developmental program is and how much innate
knowledge or behaviour it could really encode because we just don’t know enough
about how the program works or how innate knowledge and behaviour is wired into
the brain. But I think we know enough to know that the number of genes is not
the number we’re after. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">In fact, I’m not sure there is a number
that could capture what we’re after. I understand the urge to quantify the information
in the genome in some way, but it assumes there is some kind of linear scale.
For signal compression (Shannon information) or algorithmic length (Kolmogorov
complexity), you can generate such a number and use it to compare different
messages or programs. I don’t know that that’s the case for the complexity of
the brain or the complexity of the genome. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">I’m willing to say that a human brain is
more complex than that of a nematode and the human genome probably has correspondingly
more information in it than the nematode genome. But does the human genome have
<i>more</i> information than the mouse
genome or the chimp genome? Or is it just <i>different</i>
information – qualitatively, but not quantitatively distinct? Would the
Kolmogorov complexity differ between the mouse genome and the human genome? Not
much, I’d wager, and I’m not sure what you’d learn by quantifying it. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">The real problem is that none of those
measures capture what the information means, because the meaning does not
inhere wholly in the message – it depends on who is reading it and what else
they know. For example, here is a (very) short story written by Ernest
Hemingway:</span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><i><span lang="EN-GB">For sale: Baby shoes, never worn.</span></i></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">It doesn’t have much Shannon information
and you could write a very brief program to reproduce it. But it’s freighted
with meaning for most readers. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><b><span lang="EN-GB">What
does it all mean?</span></b></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">So maybe we should be asking: what is the
meaning encoded in the genome and how is that meaning interpreted and decoded
and ultimately realised? The impressive thing is that the interpretation is
done by the products of the genome itself, starting with the proteins expressed
in the egg, and then with the proteins that very quickly come to be produced
from the zygotic genome. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">The only thing physical property the genome
has to work with to encode anything is stickiness. People often say that DNA is
a chemically inert molecule that doesn’t do anything by itself and this is
accurate in the sense that it does not tend to chemically react with or form
covalent bonds with other molecules. But it is functional in a different way –
it is an <a href="https://en.wikipedia.org/wiki/Heterogeneous_catalysis">adsorption catalyst</a>. It is a surface that promotes the interaction of
other molecules by bringing them in to close proximity. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">The specific sequence of any stretch of DNA
determines which proteins will bind to it and with what affinity. If those
proteins are transcription factors or chromatin proteins then their binding may
regulate the expression of a nearby gene, as discussed above, by increasing or
decreasing the likelihood that the enzyme <a href="https://en.wikipedia.org/wiki/RNA_polymerase">RNA polymerase</a> will bind to the gene
and produce a messenger RNA molecule. And, in turn, the mRNA acts as an
adsorption catalyst, bringing transfer RNAs carrying specific amino acids into
adjacency so that a peptide bond can be formed between them, eventually forming
a specific protein. It all starts with stickiness. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Of course, what unfolds after that – after
the maternally deposited proteins bind to the genome in the fertilised egg and
the new zygote starts making its own proteins – seems almost miraculous. Those
patterns of biochemical affinity embody a complex and dynamic set of feedback
and feedforward loops, coordinating profiles of gene expression, breaking
symmetries, driving cellular differentiation and patterning of the embryo. And
the biochemical activities and affinities of the proteins produced then control
morphogenesis, cell migration, and, in the developing nervous system, the
extension and guidance of projections, and tendencies to make synaptic
connections with other cell types. </span></span></span><span style="font-size: small;"><span style="font-family: Verdana, sans-serif;">
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">So, the developing organism interprets its
own genome as it self-assembles. Pretty astounding, but that’s life
(literally). However, the ultimate interpreter of the meaning in the genome is
natural selection. The resultant organism has to be made with the right specifications,
within the right operating range so as to survive and reproduce, given the
right environmental conditions. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">You don’t need to specify where every
synapse is to get the machine to work right. You just need to specify roughly
the numbers of different cell types, their relative positions, the other types
of neurons they tend to connect to, etc. The job of building the brain is
accomplished statistically, and, crucially, probabilistically. This is why
there is lots of variation in brain structure and function even between
monozygotic twins and why intrinsic developmental variation is such a crucial
(and overlooked) source of differences in people’s psychology and behaviour
(the subject of my book <a href="https://press.princeton.edu/books/hardcover/9780691173887/innate">Innate</a>).<span> </span></span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><b><span lang="EN-GB">Back
to A.I.</span></b></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">Okay, so, where does this leave the
question we started with? Is there enough information in the genome to specify
lots of innate priors? Based on what I’ve said above, I don’t think the number
of genes in the genome places a limit on this or is even an informative number.
While I have some sympathy with efforts to define what Tony Zador refers to as
a “<a href="https://www.nature.com/articles/s41467-019-11786-6">genomic bottleneck</a>”, I’m not convinced that quantifying it will be in any
way straightforward or necessarily useful. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">It’s certainly true that there isn’t enough
information in the genome to specify the precise outcome of neural development,
in terms of the number and position and connectivity of every neuron in the
brain. The genome only encodes a set of mindless biochemical rules that, when
played out across the dynamic self-organising system of the developing embryo,
lead to an outcome that is within a range of operational parameters defined by
natural selection. But there’s plenty of scope for those operational parameters
to include all kinds of things we would recognise as innate priors. And there
is plenty of evidence across many species that many different innate priors are
indeed pre-wired into the nervous system based on instructions in the genome. </span></span></span></div>
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<span style="font-size: small;"><span style="font-family: Verdana, sans-serif;"><span lang="EN-GB">For A.I., it still may be best to try and
keep such priors to a minimum, to make a general-purpose learning machine. On
the other hand, making a true A.I. – something that qualifies as an agent – may
require building something that has to do more than solve some specific
computational problems in splendid isolation. If it has to be embodied and get
around in the world, it may need as much help as it can get.</span></span></span></div>
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the genome, which in humans is around 3 billion letters, represents an upper
bound on the Kolmogorov complexity. Only a fraction of that carries functional
information, however, so the upper KC value may be quite a bit lower than
that].</span></span></span></div>
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Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-55327789523492779152019-12-19T13:34:00.001-08:002019-12-19T13:39:32.502-08:00Is your future income written in your DNA? <div dir="ltr" style="text-align: left;" trbidi="on">
<div class="MsoNormal">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEha3E6DeK1710pyuc-lZ62Iifqtf7tXlBbf8zPzRWQ1rpn25zoPg1cK_5cj5U3cHSJvibJAZh3yyALm-SqWGNVBj-fSx7Lm9Hwm-fzUjGB2qrwWxDs1NzGEQLFhNnCFWIen0FVNKg9dsurI/s1600/profit-2395780_1920.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="1500" data-original-width="1600" height="300" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEha3E6DeK1710pyuc-lZ62Iifqtf7tXlBbf8zPzRWQ1rpn25zoPg1cK_5cj5U3cHSJvibJAZh3yyALm-SqWGNVBj-fSx7Lm9Hwm-fzUjGB2qrwWxDs1NzGEQLFhNnCFWIen0FVNKg9dsurI/s320/profit-2395780_1920.jpg" width="320" /></a><span lang="EN-GB"></span><span lang="EN-GB">A <a href="https://www.nature.com/articles/s41467-019-13585-5">newly published paper</a> makes the claim
that variation in people’s income can be partly traced to variations in their
genes. Indeed, it identifies over a hundred specific genetic variants that are statistically
associated with income in a large sample of people derived from the <a href="https://www.ukbiobank.ac.uk/">UK Biobank</a>.
To some, this idea is frankly preposterous – a naïve and outrageous over-reach
of genetic determinism and reductionism, with strains of social Darwinism. To
others, it is completely expected – not trivial, in terms of the work involved,
but certainly not at all surprising and not so earth-shattering in terms of
social implications. </span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The devil is in the details, of course, of
the methodology and the results, and, importantly, the way they are presented
and interpreted. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The idea that something like a person’s
income could be partly heritable – that is, that variation in income across the
population could be partly attributable to genetic differences between people –
is in fact, not new at all and really not remarkable at this stage. Decades of
research in behavioral genetics has clearly shown that pretty much every human
behavioral trait and every life outcome – from income to marriage to divorce
to educational attainment to going to prison – <a href="https://www.ncbi.nlm.nih.gov/pubmed/12486697">is partly heritable</a>. This is
because these experiences are partly driven by our psychological traits, which
are themselves partly driven by genetic differences. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Given the existence of these genetic
effects, it may be interesting to try and figure out the underlying mechanisms.
That starts with identifying some of the actual genetic variants that are
associated with the metric of interest in some population, and then figuring
out the causal mechanisms that link them to the phenotype. I say “may be”
interesting because it’s not actually obvious that it always is – sometimes the
details of the genes involved are very informative and others times they’re
really not. Of course, you can’t know until you look.</span></div>
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<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The paper in question, by W. David Hill and
colleagues, describes the results of a genome-wide association study (<a href="http://www.wiringthebrain.com/2015/11/what-do-gwas-signals-mean.html">GWAS</a>) of
income in a large sample of over 280,000 people from the UK (all ethnically
“white”). GWAS analyse sites in the genome where there is a common variant –
the DNA “letter” at that position may be an “A” in some people and a “C” in
others, for example. The test is simply to see if the frequency of those
variants differs in people with high income versus low income. (In the same way
that the frequency of smoking varies in people with lung cancer versus
without). GWAS look at millions of such sites (known as “SNPs”) across the
genome across the whole sample of hundreds of thousands of people. As a result
of the huge sample, these studies can detect even small differences in
frequency and differentiate significant ones from random noise. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">It was already <a href="https://www.dropbox.com/s/tl81qqmsrjb6yg7/annurev-economics-080511-110939.pdf?dl=0">well established</a> prior to
this study that income is partly heritable. What the authors wanted to do was
identify some of the causal genetic variants, see what other traits or life
outcomes might be mediating that causal connection, and illuminate the types of
genes and biological processes involved. They set out their causal model in
Figure 1 of their paper: </span></div>
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<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4px9ShDPb_XWu-Pwlhe3YzQ83mOV3eB4gClzkVdsBtglyVAdbIC3wcIH3SMcA8mb0DO_VhrZC-4zU4qOj0XeqWVYwpknA6R8DHNtK6fIfXfIu88zqkanunmuXsl4pVBSCyrk986JDHPph/s1600/Screen+Shot+2019-12-17+at+8.47.16+AM.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="842" data-original-width="1600" height="336" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4px9ShDPb_XWu-Pwlhe3YzQ83mOV3eB4gClzkVdsBtglyVAdbIC3wcIH3SMcA8mb0DO_VhrZC-4zU4qOj0XeqWVYwpknA6R8DHNtK6fIfXfIu88zqkanunmuXsl4pVBSCyrk986JDHPph/s640/Screen+Shot+2019-12-17+at+8.47.16+AM.png" width="640" /></a></div>
<br />
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<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This figure shows that the idea that income
is partly genetically driven is not so preposterous after all. It follows
directly from the fact that <a href="https://www.annualreviews.org/doi/abs/10.1146/annurev-psych-120710-100353">intelligence is strongly heritable</a>, that
intelligence is a contributing factor in educational attainment, and that
intelligence and educational attainment together contribute to what kind of job
someone gets and what they earn. None of these relationships is deterministic
or complete – they are all just partial correlations, but they’re real and
robust. When the causal pathway is shown like that, it would be amazing if
income were not partly heritable! </span></div>
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<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">(Note: That doesn’t mean that that diagram
is necessarily correct or complete, however. It makes a lot of assumptions, one
of which we know is violated. More on that below).</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The abstract sets out the findings of the
paper:</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<i style="mso-bidi-font-style: normal;"><span style="font-family: "times new roman"; mso-ansi-language: EN-US;">Socioeconomic position
(SEP) is a multi-dimensional construct reflecting (and influencing) multiple
socio-cultural, physical, and environmental factors. In a sample of 286,301
participants from UK Biobank, we identify 30 (29 previously unreported)
independent-loci associated with income. Using a method to meta-analyze data
from genetically-correlated traits, we identify an additional 120
income-associated loci. These loci show clear evidence of functionality, with
transcriptional differences identified across multiple cortical tissues, and links
to GABAergic and serotonergic neurotransmission. By combining our genome wide association
study on income with data from eQTL studies and chromatin interactions, 24 genes
are prioritized for follow up, 18 of which were previously associated with
intelligence. We identify intelligence as one of the likely causal,
partly-heritable phenotypes that might bridge the gap between molecular genetic
inheritance and phenotypic consequence in terms of income differences. These
results indicate that, in modern era Great Britain, genetic effects contribute
towards some of the observed socioeconomic inequalities.</span></i></div>
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<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, what does all this mean? Let’s take a
look at the results themselves, the conclusions based on them, and the broader
implications. </span></div>
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<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
results</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The main general findings are that income
is partly heritable and that variation in a measure of intelligence (results on
a cognitive test) partly mediates those genetic effects. I think we knew both
of those things already, and they’re certainly not surprising, but the authors
may rightly claim that this is a more explicit demonstration than has been made
previously. Because they identify some associated variants they are able to use
somewhat different approaches (such as genetic correlations and Mendelian
randomisation) to try and tease out the causal relationships.<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">I’m a little skeptical of those kinds of
analyses in this context, or at least think the conclusions we can draw from
them are somewhat limited. The idea of <a href="https://en.wikipedia.org/wiki/Genetic_correlation">genetic correlations</a> is that when you find
some genetic variants associated with one phenotype (such as income) you can
then see whether those genetic variants are also associated with another
phenotype (such as intelligence) and measure how strongly the effects of the
variants correlate across the two phenotypes. In this case, the authors find a
strong <i style="mso-bidi-font-style: normal;">genetic correlation</i> (r<sub>g</sub>=0.69)
between intelligence and income, and comparable genetic correlations between
income and health and longevity.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">That’s fine, but that number can be
misunderstood. It doesn’t imply that the actual <i style="mso-bidi-font-style: normal;">overall correlation</i> between intelligence and income is that strong.
It doesn’t imply anything about that correlation in fact. The genetic variants
collectively only “explain” a fraction of the variance in each of the two
phenotypes. That effect may well be highly correlated across the two
phenotypes, but still very minor and not sufficient to drive a strong overall
correlation between the two phenotypes. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">You see a lot of these genetic correlations
in the literature these days, because they’re easy to do, especially in
databases with rich and diverse phenotyping, like the UK Biobank. The results
can definitely be interesting and informative, but it’s worthwhile keeping the
primary effect sizes in mind when interpreting them. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The authors also use a statistical
technique called <a href="https://en.wikipedia.org/wiki/Mendelian_randomization">Mendelian randomisation</a> to try and extract a causal relationship
from what is otherwise just correlative data on genetic effects on intelligence
and income. The application of this technique here rests on some assumptions,
the main one being that variants that affect intelligence (which could thereby
affect income) do not also affect some other traits that could have independent
effects on income. The authors argue against this possibility of<span style="mso-spacerun: yes;"> </span>“horizontal <a href="https://en.wikipedia.org/wiki/Pleiotropy">pleiotropy</a>” in their discussion
of limitations of the study, but it seems very difficult to rule it out. That’s
not to say there’s really any reason to doubt that model, as it is inherently
plausible, and a wealth of data shows that intelligence partially correlates
with future earnings. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Beyond those general points, the main
novelty of the paper lies in the identification of specific SNPs that are
associated with the phenotype of income. As mentioned, many of these are also
associated with intelligence, which is argued to be the causal mediator. When
you find an associated SNP (or multiple ones in a small region) you can often
deduce what gene is likely affected by those genetic variants. The authors
identify 144 genes in this way that harbour genetic variants statistically
associated with income.<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">What
kinds of genes are involved?</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, what kinds of genes are they? What are
their normal functions? Well, the first thing to note is that they are highly
enriched for genes expressed in the nervous system. That’s good news,
methodologically speaking, because it provides a crucial reality check. One
danger in performing GWAS for a social phenotype like income is that that
average income might vary geographically across the country. (In fact, we know
it does for the UK). This means you could pick up SNP associations that are
really tracking local differences in ancestry, rather than anything in a real
causal chain to the phenotype. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The authors use a number of statistical
methods to control for that problem but there’s always a worry that <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879529/">such measures are insufficient</a>. However, if the GWAS signals were just
due to cryptic population stratification you would not expect enrichment for
any specific classes of genes – just signals all over the genome with no
biological meaning and possibly no biological effect at all. So, the enrichment
for neural genes strongly argues that the signals detected are real and also
fits with the favoured explanation that intelligence is a causal mediator. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Beyond that, however, there’s not really a
lot that can be said about these genes that is particularly illuminating. First, the
associated genes were not enriched for any particular biochemical functions. Second, the
authors use a variety of gene expression datasets to look for any enrichment of
associations in genes with higher expression in particular parts of the brain
or cell types. And they do come up with some statistically significant
enrichments, but, to be frank, as a neuroscientist, I don’t know what to make
of that information. I think probably nothing.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span lang="EN-GB">For example, the associated genes show
enrichment for “</span><i style="mso-bidi-font-style: normal;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">expression
differences in cerebellar hemisphere, at Brodmann area 9 (BA9) of the frontal
cortex, the nucleus accumbens and at Brodmann area 24 of the anterior cingulate
cortex (BA24)</span></i><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">”. These findings rely on databases of gene expression
profiles across the brain. But most genes are expressed in many different areas
(many in all). Some are a bit higher in some areas than others, but that does
not mean their function is restricted to the areas with higher expression. Those
statistical descriptors do not reflect the true richness and dynamics of gene
expression in the brain. And the data presented in this paper are statistical
enrichments of those statistical enrichments (i.e., there’s a bit more signal
in genes that are expressed a bit more in those areas). It is highly doubtful
that the genetic effects on income (via intelligence or other psychological
traits) are mediated in any specific way (or even predominantly) by changes in
those highlighted brain areas.<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The same can be said for the data on cell
type enrichments:</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<i style="mso-bidi-font-style: normal;"><span style="color: black; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">“Cell-type-specific analysis revealed that the expression that was
specific to the serotonergic neurons and to medium spiny neurons was associated
with income. Medium spiny neurons have previously been linked to schizophrenia,
which has a strong cognitive component and has previously been linked to
glutamatergic systems, including the N-methyl-D-aspartate receptor signalling
complex. Medium spiny neurons are a subtype of GABAergic inhibitory neurons.
Future work should examine if, like other cognitive traits, income is linked to
both GABAergic and glutamatergic systems.”</span></i></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This is a strange way of working round to
the idea that maybe the two major classes of neurons in the brain are involved
somehow. In any case, the same problems apply as with the brain area expression
data – the real patterns of gene expression are simply not that specific. Cell
types are defined by combinatorial profiles of gene expression, and most
individual genes are expressed all over the place in many different cell types,
in complex and dynamic ways. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">I don’t mean to be overly critical of the
attempts. These kinds of analyses might have thrown up some specific information
– they certainly have for other kinds of phenotypes. But for complex
psychological phenotypes, which really reflect the function or performance of
the whole brain, we should not expect any anatomical or cell-type specificity,
and my interpretation of the data presented in this paper is that, while there
are some statistically significant signals, they are not biologically
meaningful. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Finally, the authors integrate various
sources of data to focus on a subset of the genes that seem most likely to have
genetic variants directly affecting expression in the brain. They say: “</span><i style="mso-bidi-font-style: normal;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">These 24 genes therefore should be prioritized in
follow-up studies”. </span></i><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">It’s not obvious what such follow-up studies might
entail. The effects of each of the variants on the phenotypes of interest are
individually almost negligible, and provide <a href="http://www.wiringthebrain.com/2018/11/life-after-gwas-where-to-next-for.html">no real experimental purchase</a>. Of course one can look at the effects of the genetic
variants on expression of the genes, and one can perform various studies to try
and figure out what the normal functions of those genes is, at a biochemical or
cellular or developmental level. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">But t</span><span lang="EN-GB">hat is a very different
question from asking what are the <i style="mso-bidi-font-style: normal;">effects
of genetic variation in the gene</i>. These effects can be very <a href="https://aeon.co/ideas/wired-that-way-genes-do-shape-behaviours-but-its-complicated">non-specific</a>
and not really related to what you would say the function of the gene is. The genomic program of brain development involves lots of genes
with specific developmental functions but also relies on maybe ten-fold more
genes with much <a href="http://www.wiringthebrain.com/2018/02/lessons-for-human-genetics-from-genetic.html">more generic functions</a> – not really part of the instructions of
brain development per se, just general stuff required for everything to go
right (like metabolic enzymes, for example). Most of the genetic variants affecting brain development will thus
be doing so indirectly and non-specifically (and non-informatively). </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, I am not convinced that the
identification of these associated genes actually sheds much light on the
underlying biology driving the association with income (via intelligence or
otherwise), except to reinforce the idea that those kinds of psychological
traits are really emergent properties of the whole neural system and can’t
necessarily be tied to specific molecular systems.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
conclusions</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span lang="EN-GB">The final line of the abstract states: “</span><i style="mso-bidi-font-style: normal;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">These results indicate that, in modern era Great
Britain, genetic effects contribute towards some of the observed socioeconomic
inequalities.</span></i><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">” This is clearly the intended take-home message. </span><span lang="EN-GB">And it is true, in a literal sense, (if the main results are methodologically
sound, as they seem to be), but also a bit misleading and open to
misinterpretation. A more accurate statement would be that “</span><i style="mso-bidi-font-style: normal;"><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">genetic effects</span></i><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";"> <i style="mso-bidi-font-style: normal;">contribute
a minor amount towards some of the observed socioeconomic inequalities”. </i></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Based on their calculations, the total
heritability of income that can be tagged by common genetic variants in the
population sample under study is only 7.4%. And using polygenic scores based on
the results of the GWAS to predict income in an independent sample only
explained 2% of the variance. Given that, the unqualified wording of the
abstract leaves open the possibility of people interpreting the effects as
larger than they really are. (And then running with that interpretation to make
all kinds of other claims). </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Note that the overall genetic effect may in
fact be a good bit larger, as twin studies have estimated the total heritability
of income at 40-50%. These studies account for non-genetic familial effects, in
that these should be shared equally between twins regardless of whether they
are monozygotic or dizygotic. The observation is that pairs of MZ twins are
much more similar in income than DZ twins, implying a genetic effect. A likely
explanation for why the current study could not account for all of that
heritability is that much rarer genetic variants are <a href="http://www.wiringthebrain.com/2019/04/missing-heritability-found-safe-and-well.html">responsible for much of it</a>. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">However, it is extremely important to
emphasise that the heritability is not a fixed number. There is no right
answer. It only measures the proportion of phenotypic variance that can be
attributed to genetic differences <i style="mso-bidi-font-style: normal;">within
the population sample</i> actually being studied. It cannot be generalised to
other populations or taken as a sweeping statement of truth. Variation in a
social measure like income can obviously be hugely dependent on social and
cultural factors – much more so in some settings than others. If you take a
very culturally homogeneous sample, where the variation in such social and
cultural factors is low, then the heritability of the trait will be
correspondingly higher (because it is a proportion). But across more diverse
social samples, the heritability could be much lower. And heritability within
one population says nothing – at all – about the origins of differences between
populations.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">A concern is that people will take only the
widest, most sweeping interpretation of the results described here to bolster
the argument that socio-economic success is simply meritocratic, in the sense
that it is determined in some simple way by people’s innate intellectual
abilities and aptitudes. (See here for <a href="https://www.irishtimes.com/news/education/what-makes-children-smart-genes-or-environment-1.4080624">an example</a> of such an argument). The reality is vastly more complex. Not only are environmental factors
hugely important, but they interact with genetic factors in complex, non-linear
ways.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This is where the authors’ basic model as
presented in Figure 1 is too simple, in my view. The models used to partition
variance assume that the effects of genetic and environmental factors will be
independent of each other and will simply add up. It’s difficult to determine
whether or not the assumption of additivity actually holds in a study like
this, but it <a href="https://www.ncbi.nlm.nih.gov/pubmed/24002887">seems likely</a> that the effects of some
environmental factors will vary depending on a person’s genetic make-up, and
vice versa. But more importantly, there are correlations between a person’s
genes and the environment they experience. These arise because they share genes
with their parents, who partly create the environment for their children. I
think a more accurate causal pathway diagram would look like this:</span></div>
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<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQESSOf_q-hTDGC3oT9IIDzeHsy9U6toyh3UOB38AZIBWnOxRkBTHqzrXdmfuN5LcYc83BTCqzG8MpSdqgRgtBkO8-r6TddfAquDIHQBy2iQ31MUwHOattbaXh-82x6reZQvHBLP4FhsFp/s1600/rGE-income.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1131" data-original-width="1600" height="452" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQESSOf_q-hTDGC3oT9IIDzeHsy9U6toyh3UOB38AZIBWnOxRkBTHqzrXdmfuN5LcYc83BTCqzG8MpSdqgRgtBkO8-r6TddfAquDIHQBy2iQ31MUwHOattbaXh-82x6reZQvHBLP4FhsFp/s640/rGE-income.jpg" width="640" /></a></div>
<br />
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<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span lang="EN-GB">The authors do say that they cannot rule
out such dynastic effects (gene-environment correlations across generations) as
a possible confounder and refer to <a href="https://science.sciencemag.org/content/359/6374/424">another paper</a> that suggests they may be
especially important in analyses of the genetics of educational attainment</span><span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">. The problem is the magnitude of such effects is extremely
difficult to calculate in the population study design employed. </span></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">This means the straightforward causal pathway – where
the genetics of the individual drives the heritability of income – is likely
too simple. The real scenario is sure to involve complex positive feedback
loops that <a href="https://theconversation.com/nature-versus-nurture-how-modern-science-is-rewriting-it-127472">entangle and amplify</a> the effects of genetic endowments and social
capital over generations.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Finally, the authors add these important
caveats on how their results should be (and should not be) interpreted:</span></div>
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<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<i style="mso-bidi-font-style: normal;"><span style="color: black; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">“A further limitation is that molecular genetic analyses of phenotypes,
such as intelligence, income or SEP, appear prone to being misinterpreted. Such
misunderstandings include describing associated variants as genes for income,
or the misinterpretation that any associated variant, and indeed any nonzero heritability
estimate, is evidence for genetic determinism or the immutable nature of these
phenotypes via environmental intervention. We include a figure (Fig. 1) that
illustrates that genetic variants do not act directly on income; instead,
genetic variants are associated with partly heritable traits (such as
intelligence, conscientiousness, health, etc.), which have their own complex
gene-to-phenotype paths (including neural variables) and are ultimately associated
with income. Therefore, the genetic variant–income associations discovered here
are no more for income than they are for these other traits. For more
discussion of the implications of these results, aimed at the general reader,
we have provided a Frequently Asked Questions (FAQ) document in Supplementary
Note 2.”</span></i></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The FAQs are very useful, but it seems
unlikely that many readers will actually even notice they exist or go to the
trouble of digging them out, meaning that despite these efforts by the authors,
these findings are sure to be misinterpreted and misrepresented. I do think
some of the plainer language and important disclaimers in the FAQ answers could
have been included in the main text to better pre-empt misunderstandings. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">I’m sure this paper will continue to
attract a lot of attention and we will see more studies like it (like <a href="https://www.nature.com/articles/s41562-019-0757-5">this one</a>,
for example) that explore the potentially fraught areas of genetic effects on
complex social outcomes. </span></div>
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<span lang="EN-GB"> </span><span lang="EN-GB"></span><span lang="EN-GB"> </span>
</div>
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-->Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-50745938425392463112019-09-14T05:18:00.001-07:002019-09-14T05:18:26.296-07:00Beyond reductionism – systems biology gets dynamic<div dir="ltr" style="text-align: left;" trbidi="on">
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<div class="MsoNormal">
<span lang="EN-GB"></span><span lang="EN-GB">Is biology just complicated physics? Can we
understand living things as complex machines, with different parts dedicated to
specific functions? Or can we finally move to investigating them as complex,
integrative, and dynamic systems? </span>
</div>
<div class="MsoNormal">
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjL5jCojo0ukT0vrPX9IDzRIb9MVPXYUyl7JECS0nWJJzL-J6pRn-SH2dXRYc5hua2GX20-hMKxCiHyWcWjt8lHCzzA-ywuX1cDvU45UOuUpZ2Mf3bjKME0lMqUBKQL-TaHJAU5MalYZzYG/s1600/attractor.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="300" data-original-width="297" height="200" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjL5jCojo0ukT0vrPX9IDzRIb9MVPXYUyl7JECS0nWJJzL-J6pRn-SH2dXRYc5hua2GX20-hMKxCiHyWcWjt8lHCzzA-ywuX1cDvU45UOuUpZ2Mf3bjKME0lMqUBKQL-TaHJAU5MalYZzYG/s200/attractor.png" width="197" /></a></div>
</div>
<div class="MsoNormal">
<span lang="EN-GB">For many decades, mechanistic and reductionist
approaches have dominated biology, for a number of compelling reasons. First,
they seem more legitimately scientific than holistic alternatives – more
precise, more rigorous, closer to the pure objectivity of physics. Second, they
work, up to a point at least – they have given us powerful insights into the
logic of biological systems, yielding new power to predict and manipulate. And
third, they were all we had – studying entire systems was just too difficult. All
of that is changing, as illustrated by a flurry of recent papers that are using
new technology to revive some old theories and neglected philosophies.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The central method of biological <a href="https://plato.stanford.edu/entries/scientific-reduction/">reductionism</a>
is to use controlled manipulation of individual components to reveal their
specific functions within cells or organisms, building up in the process a
picture of the workings of the entire system. This approach has been the
mainstay of genetics, biochemistry, cell biology, developmental biology, and
even neuroscience. When faced with a system of mind-boggling complexity, it
makes sense to approach it in this carefully defined, controlled manner. In any
case, in most of these fields it was technically only possible to manipulate
one or a few components at a time and only possible to measure their effects on
one or a few components of the system. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The productivity of reductionist methods,
and the lack of viable alternatives, brought with it a widespread but often
tacit commitment to <i style="mso-bidi-font-style: normal;">theoretical</i>
reductionism – the idea that the whole really is not much more than the sum of
its parts. Appeals to holism seem to many biologists not just out of reach
technically, but somehow vague, fuzzy, and unscientific. We are trained to
break a system down to its component parts, to assign each of them a function,
and to recompose the systems and subsystems of organisms and cells in an
isolated, linear fashion. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">We can see this in genetics, with the
isolation of a gene for this or a gene for that. Or in signal transduction,
with the definition of linear pathways from transmembrane receptors, through
multiple cytoplasmic relays, to some internal effectors. Or in neuroscience,
with the assignment of specific and isolated functions to various brain
regions, based on lesion studies or activation in fMRI experiments. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The trouble is that is not how cells and
organisms work. Defining all these isolated functions and linear pathways has
been productive, but only from a certain perspective and only up to a point.
This enterprise has mostly depended on analysing responses to strong
experimental manipulations – a trusted method to perturb the system but one
that is inherently artificial (what <a href="https://en.wikipedia.org/wiki/Francis_Bacon">Francis Bacon</a>, the so-called father of
empiricism, called “vexing nature”)*. And it has mostly analysed effects on limited,
pre-defined readouts. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">That’s all fine – strong manipulations that sensitise a
system can reveal roles of specific components in some process that would
otherwise be undetectable. The problem comes in forgetting how artificial these
scenarios are and in inferring greater specificity and isolation than really
exist. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The failure of so many drug trials
highlights the hubris of thinking that reductionist manipulations and analyses
reveal biological systems as they really are. We tend to focus on the standout
successes, as validation of the whole enterprise, but the <a href="https://www.ncbi.nlm.nih.gov/pubmed/29394327">hit rate is tiny</a>,
even for candidates with exhaustive pre-clinical support. </span></div>
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<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Systems
in the wild</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Real biological systems – in the wild, as
it were – simply don’t behave as they do under controlled lab conditions that
isolate component pathways. They behave <i style="mso-bidi-font-style: normal;">as
systems</i> – complex, dynamic, integrative systems. They are not simple
stimulus-response machines. They do not passively process and propagate signals
from the environment and react to them. They are <a href="https://en.wikipedia.org/wiki/Autopoiesis">autopoietic</a>, <a href="https://en.wikipedia.org/wiki/Homeostasis">homeostatic</a>
systems, creating and maintaining themselves, accommodating to incoming information
in the context of their own internal states, which in turn reflect their
history and experiences, over seconds, minutes, hours, days, years, and which even
reflect the histories of their ancestors through the effects of natural
selection.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Living things <i style="mso-bidi-font-style: normal;">do things</i> – they are proactive agents, not merely reactive systems.
This is widely acknowledged in a general sort of way, but the problem is that
the conceptualisation of cells or organisms as proactive systems has remained
largely philosophical, even metaphorical, and disconnected from experimental
study. It’s just not easy to study cells or organisms <i style="mso-bidi-font-style: normal;">as systems</i>. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Systems biology was intended to take a Big Data-driven
holistic approach, but until recently, had failed to fully divest itself from static,
reductionist thinking and embrace an <a href="https://en.wikipedia.org/wiki/Enactivism">enactive</a>, <a href="https://en.wikipedia.org/wiki/Dynamical_system">dynamical systems</a> framework.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Big data alone do not solve the problem,
without some dynamical systems theoretical underpinning to how they are
analysed. In genomics, for example (or transcriptomics, proteomics,
methylomics, whatever omics you’re having yourself), new technologies allowed
researchers to assess the state of vast numbers of molecular entities, under
various conditions. But these approaches simply produced ranked lists of
thousands of genes or transcripts or proteins and then the question was: what
to do with them? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">One thing is to look for some kinds of
patterns or cross-correlations in the data, which can serve to implicate
various genes or proteins in related pathways or processes, through guilt by
association. This can certainly be informative, but has its limits – it doesn’t
tell us how a gene or protein functions in any given process nor how that
process actually works. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">A complementary approach is to focus on
specific molecules for experimental follow-up using reductionist methods. Faced
with such extensive lists, the chosen molecules were typically the ones already
implicated by some prior evidence (the “go down the list and pick the one you
would have studied anyway” approach), creating a rather circular chain of logic
and not necessarily deepening understanding of the system as a whole. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Network analyses promised a more holistic
perspective, but these have tended to remain very much at the descriptive
level. Given a list of molecular entities under several conditions, it is
possible to generate <a href="https://en.wikipedia.org/wiki/Network_theory">network graphs</a> based on their pairwise cross-correlations
or some other statistical interaction. By themselves, these analyses simply
cough up colourful hairball diagrams. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://magazine.utoronto.ca/research-ideas/science/hairball-infoball-brenda-andrews/"><img alt="https://magazine.utoronto.ca/research-ideas/science/hairball-infoball-brenda-andrews/" border="0" data-original-height="320" data-original-width="480" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1XKZpD6hZwxtn9xJaMLUowPuJmEAqJfs1KICNiOJAp6ZXVjvEUSVmZGi3ki3l6yi6c8BCmmHhHSiCFODXw8ObDuNQAja17-mZTx21rbw0PhBTNNARRtVIODW27i8Elsq23Vu6IkIVEncx/s400/hairball.jpg" width="400" /></a></div>
<br />
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">However, it is possible to analyse these network
graphs to define many different kinds of parameters of local and global
connectivity, such as degree of modularity, efficiency of information transfer,
and so on. In my view, these sorts of structural descriptors are not
particularly illuminating. It’s not really clear what you can do with those
figures, except compare them, but then the major message seems to be that most
networks tend to have broadly similar properties (<a href="https://en.wikipedia.org/wiki/Small-world_network">small-world</a> connectivity, a
few well connected hubs, etc.). </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">What is missing from these analyses is any
sort of dynamics or an idea of what the system is doing. A step in the right
direction is the definition and recognition of <a href="http://www.wiringthebrain.com/2017/09/what-are-laws-of-biology.html">functional motifs</a>. Elements in
biological networks (such as genes or proteins or neurons) are not just connected
any old way. The connections often have a sign – they may be activating or
repressing, excitatory or inhibitory. And they also have an architecture – they
may be feedforward or feedback or autoregulatory. If you connect elements of
different signs in different mini-architectures, you get functional motifs –
little units that can perform certain types of operations. (Well, most of the
time you get nothing – only a small subset of all possible combinations is
actually functional, and an even smaller subset is robustly so). </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">These kinds of functional motifs can be
recognised in an abstract sense, in whatever kind of network you are looking at.
They can act as filters, amplifiers, switches, coincidence detectors, evidence
accumulators, error predictors, oscillators, and so on. By analysing the
structure and nature of interactions between elements of a network (like
transistors on a chip) it is possible to identify such motifs and infer something
about what kind of operations that little subsystem can perform. And, of
course, you can build more complicated systems out of these functional units. </span></div>
<br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkUdO6Y7JE9RlrGSIaS8LIO8a4zskgKwFgCeBdqlVV1-cAmb2b6KhfVn1iwTLATze1yyeP_wcJCo5Rp9X8CODIG_r-iNcJRZfR9whkPij7obDwRnR3JLu7hcAZ6aGVvFeqYMyAUeWq4BGr/s1600/network+motifs-2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="720" data-original-width="960" height="300" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkUdO6Y7JE9RlrGSIaS8LIO8a4zskgKwFgCeBdqlVV1-cAmb2b6KhfVn1iwTLATze1yyeP_wcJCo5Rp9X8CODIG_r-iNcJRZfR9whkPij7obDwRnR3JLu7hcAZ6aGVvFeqYMyAUeWq4BGr/s400/network+motifs-2.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Reproduced from this really nice <a href="https://slideplayer.com/slide/10326065/">presentation</a> by Kimberly Glass</td></tr>
</tbody></table>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">These structures don’t just pop out of
cross-correlation data, however. Usually it requires more defined reductionist
experiments to supply the necessary data. In addition, while such analyses
promise some insight into what bits of a system can do, in the abstract, they
don’t show you what the system, <i style="mso-bidi-font-style: normal;">as a
whole</i>, actually does – either how it behaves, as a collective, or what that
system behaviour correlates with. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">To do that, we would ideally like to track
the state of all the elements of a system over time (how much each gene is
being expressed or how much each neuron is active, for example), correlate that
state with some external measure (like cellular phenotypes, or organismal
behaviour), and deduce some global functional relationships. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Revealing
the dynamics</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This presents both technical and
computational challenges, as well as a deeper philosophical challenge – what is
the right way to think about how biological systems work? This is where a
number of recent studies have proved so exciting – to me at least – as they
have tackled the technical and computational challenges with incredible
ingenuity, and, in the process, are helping to give some concreteness and
experimental testability to the enactive, dynamical systems perspective and a
<a href="https://en.wikipedia.org/wiki/Process_philosophy">philosophical approach</a> rooted in process rather than substance. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Impressive new technologies are meeting the
challenge of collecting the kinds of data we need. For example, <a href="https://en.wikipedia.org/wiki/Single_cell_sequencing#Single-cell_RNA_sequencing_(scRNA-seq)">single-cell RNA sequencing</a> can give a profile of the expression level of all the 20,000 or so
genes across large numbers of individual cells in a sample, under various
conditions or at various time-points during differentiation. Similarly,
advances in genetically encoded <a href="https://www.nature.com/articles/nn.4359">calcium or voltage indicators</a> and <a href="https://www.nature.com/articles/s41592-018-0266-x">miniscopes</a>
(or other recording approaches) allow the recording of neural activity patterns
across large numbers of neurons in awake, behaving animals. In both these types
of scenarios, a huge amount of data is generated that effectively captures the
state of the system across time. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The problem is those data are vastly
high-dimensional. Each snapshot is a matrix of the present state of N elements,
with the state of each element potentially changing at each measured
time-point. The challenge is to identify the meaningful patterns within those
high-dimensional data.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">There are many possible approaches to this
problem but one that has emerged recently, across diverse fields, involves
mapping these data to a low-dimensional “<a href="https://www.simonsfoundation.org/2019/07/31/searching-for-the-hidden-factors-underlying-the-neural-code/">manifold</a>”. In essence, this relies on
a kind of <a href="https://en.wikipedia.org/wiki/Principal_component_analysis">principal components analysis</a> – extracting statistical patterns that
capture much of the important variance that is correlated with some external
parameter. </span><br />
<br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8Sz0mox3WOOZKhyQVgys-TRBkD4jTRcsA2oC5baQPOXvG5jQBxOsDNgrvJ2ZZGfBHwAl2360Y1P6jkQZzDpyZOsLFOBpR4hejo4YO_BQmZiP866VXn8oanLmIG6XLMwqY4L_bQScR7tBx/s1600/Screen+Shot+2019-09-14+at+1.16.13+PM.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="762" data-original-width="1600" height="190" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8Sz0mox3WOOZKhyQVgys-TRBkD4jTRcsA2oC5baQPOXvG5jQBxOsDNgrvJ2ZZGfBHwAl2360Y1P6jkQZzDpyZOsLFOBpR4hejo4YO_BQmZiP866VXn8oanLmIG6XLMwqY4L_bQScR7tBx/s400/Screen+Shot+2019-09-14+at+1.16.13+PM.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">From <a href="https://www.ncbi.nlm.nih.gov/pubmed/30877963">Saxena and Cunningham</a>, 2019</td></tr>
</tbody></table>
</div>
<div class="MsoNormal">
<br />
<span lang="EN-GB">This is only possible because <i style="mso-bidi-font-style: normal;">there is</i> actually low-dimensional
structure in the state of the system. Most complex dynamical systems,
characterised by a network of simultaneously acting feedback interactions, can
only stably exist in a tiny fraction of all the mathematically possible states
of the system – so-called <a href="https://en.wikipedia.org/wiki/Attractor">attractor states</a>. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">If we think of a system with just two
elements, A and B, we can imagine what will happen if A represses B and vice versa,
and each of them activates itself. The system can exist in a state of high A
and low B, or low A and high B, but not any other states. Now expand that
thinking, but to many thousands of elements, with many thousands of interacting
feedback loops. These interactions place massive constraints on the possible
states of the system, and, additionally, on the dynamics of the system – how it
tends to transition from one state to the next. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Reducing the dimensionality of the data can
thus reveal the underlying dynamics of the system as it moves from one state to
another. If these states correspond to something – if they <i style="mso-bidi-font-style: normal;">mean something</i> – then this approach can illuminate not just the
myriad details of what is happening in the system, but allow us to make sense
of <i style="mso-bidi-font-style: normal;">what it is doing</i>. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Attractor
states and dynamic trajectories in neuronal networks</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">In neuroscience, this approach was
championed by <a href="https://www.cell.com/neuron/fulltext/S0896-6273(17)30363-X?code=cell-site">Walter Freeman</a> in the 1960-1980’s, inspired by his work in the
olfactory system. He and his colleagues recorded the responses to various
odorants in many neurons at a time in the olfactory bulb of rodents. They
discovered that the responses of individual cells were noisy and unreliable,
but the responses of the system as a whole had a <a href="https://slideplayer.com/slide/4997051/">discernible structure and dynamics</a>, in that the odorants could be deduced by the experimenters from the
dynamic trajectory of the patterns of neuronal activation through system space
over some short time period. </span></div>
<div class="MsoNormal">
<br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjKB3puibwtS_tk8tflqkUfcFFITx9bRyQgufjxbUcXhzpfxJBeCbV8uySfqr8lTItPcRvDydSd19nD7aKxmMvkC3dBBVlr5-CDiPGQyw2Ynl1FDp-ro_2fy12VWGE2M3v-a8ju-SupvQKn/s1600/freeman+olfactory-2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="435" data-original-width="666" height="261" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjKB3puibwtS_tk8tflqkUfcFFITx9bRyQgufjxbUcXhzpfxJBeCbV8uySfqr8lTItPcRvDydSd19nD7aKxmMvkC3dBBVlr5-CDiPGQyw2Ynl1FDp-ro_2fy12VWGE2M3v-a8ju-SupvQKn/s400/freeman+olfactory-2.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Taken from <a href="https://slideplayer.com/slide/4997051/">presentation</a> by Walter Freeman</td></tr>
</tbody></table>
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Subsequent work by <a href="https://www.ncbi.nlm.nih.gov/pubmed/8931275">Gilles Laurent</a> and
others reinforced this idea. It has always seemed to me to be a powerful and
insightful method to describe what a neural system is doing and understand what
kind of information it is encoding and what sorts of things it cares about. But
it never replaced the prevailing reductionist paradigm in neuroscience of
linear, hierarchical signal processing, and I have rarely seen it extended
beyond simple sensory systems. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">That is definitely changing, with some
recent compelling examples enabled by new technologies that allow researchers to
record from very large numbers of neurons at once in awake, behaving animals,
and new computational methods to analyse the data, including machine learning
approaches to extract the meaningful, low-dimensional patterns. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">These include, for example,
characterisation of the attractor dynamics of <a href="https://www.nature.com/articles/s41593-019-0460-x">head-direction cells</a> in
rodents,<span style="mso-spacerun: yes;"> </span>the flow and modulation of <a href="https://www.ncbi.nlm.nih.gov/pubmed/30664771">human cognitive states</a></span><span lang="EN-GB"> and Bayesian inference<a href="https://www.ncbi.nlm.nih.gov/pubmed/31320220"> in monkeys</a>.</span><span lang="EN-GB"> </span><span lang="EN-GB">These approaches are nicely reviewed <a href="https://www.ncbi.nlm.nih.gov/pubmed/31426024">here</a>
and <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=30877963">here</a>, and harken back to Freeman’s seminal work,
described in his book: <a href="https://cup.columbia.edu/book/how-brains-make-up-their-minds/9780231120081">How Brains Make Up Their Minds</a> (2001, Columbia
University Press.
</span> </div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
resurrection of Waddington’s landscape</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Similarly, in the study of development, new
technologies are reviving some old concepts. In the 1950’s, <a href="https://en.wikipedia.org/wiki/C._H._Waddington">Conrad Waddington</a> introduced
the ‘<a href="https://en.wikipedia.org/wiki/C._H._Waddington#Epigenetic_landscape">epigenetic landscape</a>’ as a visual metaphor to help understand the
transitions in cellular differentiation during development of an organism. (And
no, it’s not <a href="http://www.wiringthebrain.com/2013/01/the-trouble-with-epigenetics-part-1.html">that kind</a> of epigenetics). This metaphor depicted a ball rolling
down a landscape with a series of forking valleys, or channels. The ball
represented a cell and each of the channels represented a possible cell ‘fate’
that it could differentiate into, while the ridges between them represent
unstable states. The ball can also represent the whole organism, with the
various channels representing different phenotypic states. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"> <table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhLHbusdPjCxBg6rX_p-ASoTYYgVBcqPQrGuFMqnCNXJnJOGJktGdsnPE6Bhk5flJn4pMXJlSZtnwGoqEJYsOgCAe9LY-MHibDT2oi56lvRaC8Hqqp0zL5w-hCLEmu6UPvdWxUk8X7_Q-_S/s1600/Waddington+landscape.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="555" data-original-width="1600" height="220" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhLHbusdPjCxBg6rX_p-ASoTYYgVBcqPQrGuFMqnCNXJnJOGJktGdsnPE6Bhk5flJn4pMXJlSZtnwGoqEJYsOgCAe9LY-MHibDT2oi56lvRaC8Hqqp0zL5w-hCLEmu6UPvdWxUk8X7_Q-_S/s640/Waddington+landscape.png" width="640" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">From "<a href="https://press.princeton.edu/titles/13255.html">Innate</a>" (Kevin Mitchell, Princeton University Press, 2018)</td></tr>
</tbody></table>
</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The landscape is shaped by all of the
cross-regulatory interactions between all of the genes in the organism. The
contours of this landscape will vary from individual to individual due to
genetic variation. As a result, the developing organism may be more likely to
be channelled down one pathway or another in one individual versus another,
with the outcome in any specific case being influenced by noise in the system
or external forces. This can help explain the probabilistic inheritance of
<a href="https://www.frontiersin.org/articles/10.3389/fgene.2017.00048/full">complex diseases</a>, where differential <i style="mso-bidi-font-style: normal;">risk</i>
can be inherited, but the actual outcome is not genetically determined. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Sui Huang provided a nice update and
partial mathematical formalisation of Waddington’s framework in an <a href="https://www.ncbi.nlm.nih.gov/pubmed/22102361">insightful paper</a> from 2011,
but there have been few rigorous experimental studies that have fleshed out
this approach.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">A <a href="https://science.sciencemag.org/content/365/6455/786.abstract">new study</a> by Thomas Norman and
colleagues, from the lab of Jonathan Weissman provides an impressive
experimental test of this framework. They used a CRISPR-based technique to
over-express hundreds of regulatory genes, in pairwise combinations, in
mammalian tissue culture cells, and analysed their effects on the
transcriptional state of all of the genes in the genome using single-cell RNA
sequencing during growth and differentiation. They then used computational
techniques to extract a low-dimensional manifold that captured much of the
variation in the landscape of genetic interactions across all these
manipulations. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This genetic interaction manifold revealed
convergence onto a small set of biological processes, perturbation of which had
definable effects on the transcriptional profile and differentiation
trajectories of the cells. It highlighted the functional nature of genetic
interactions and suggested new ones, which were experimentally verified. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This paper thus puts some experimental meat
on the conceptual bones of Waddington’s landscape. In particular, it allowed
the researchers to measure how different genetic variants can shape that
landscape, singly and in combination. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Crucially, it is not just an analysis of
the transcriptional states underlying different cell types (i.e., which genes
are turned on or off in the formation of a muscle cell or a skin cell or a
nerve cell). It describes how those developmental pathways are affected by
genetic perturbations. In this case it was an experimental over-expression of
specific genes, but the same logic applies to the effects of naturally
occurring genetic variations, whether they increase or decrease gene function. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This sort of approach thus provides some
hope of finally getting a handle on the high-dimensional, non-linear (or
epistatic) <a href="http://www.wiringthebrain.com/2013/07/no-gene-is-island.html">genetic interactions</a> that underlie the relationship between whole
genotypes and phenotypes. The phenotypic effects of any particular genetic
variant are massively constrained by all the gene regulatory interactions
encoded in the genome (which are evolved to <a href="https://press.princeton.edu/titles/8002.html">robustly channel development</a> into
certain outcomes) and by the simultaneous effects of all the other genetic
variants present in the genome. These can collectively push the system into new
territory and even reveal novel attractor states in phenotypic space, some of
which may be pathological. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Up till now we have only been able to get a
statistical or averaged view of these genetic effects. The computational
approach of defining low-dimensional manifolds may allow us to understand the
outcome of all these effects by following what are likely to be highly
prescribed trajectories through phenotypic state space. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">A
philosophical shift</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">All of these examples suggest we are
watching a paradigm shift in real time: systems biology is finally embracing
dynamics and, in the process, providing the means to turn vast quantities of
data into real knowledge, deepening our understanding of what living systems
are doing. The success of these findings should help to rehabilitate holistic,
enactive approaches in the minds of scientists wedded to what they see as the
rigour of reductionism. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"><a href="https://en.wikipedia.org/wiki/Enactivism">Enactivism</a> sees organisms as creating their
own reality through dynamic interaction with their environment, assimilating
information about the outside world into their own ongoing dynamics, not in a
reflexive way, but through active inference, such that the main patterns of
activity remain driven by the system itself. This perspective is well described
by <a href="https://mitpress.mit.edu/books/embodied-mind-revised-edition">Varela, Thompson and Rosch</a></span><span lang="EN-GB">, and developed by Evan Thompson in his
2007 book <a href="https://www.hup.harvard.edu/catalog.php?isbn=9780674057517">Mind in Life</a>, and by others, including Alicia Juarrero (<a href="https://mitpress.mit.edu/books/dynamics-action">Dynamics inAction</a>) and Andy Clark (<a href="https://global.oup.com/academic/product/surfing-uncertainty-9780190217013?cc=ie&lang=en&">Surfing Uncertainty</a>), for example. But outside of
philosophical circles (especially philosophy of mind and related areas of
cognitive science) these ideas have not had the revolutionary impact one might
have expected. </span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Biology textbooks do not present<a href="https://thebiologist.rsb.org.uk/biologist-opinion/159-biologist/opinion/1882-what-are-the-laws-of-biology"> this view of life</a> and biologists rarely teach it to students. The reasons can perhaps be
traced back to the adoption of the mechanistic perspective in Western science,
following the successes of Newtonian mechanics, and the accompanying tradition
of reductionism. This can be set against a very different conceptual tradition
of process philosophy, as championed by Alfred North <a href="https://en.wikipedia.org/wiki/Alfred_North_Whitehead">Whitehead</a> in the early
1900’s. (<a href="https://www.amazon.com/Science-Modern-World-Alfred-Whitehead/dp/0684836394">Science and the Modern World</a>).</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"><a href="https://en.wikipedia.org/wiki/Process_philosophy">Process philosophy</a> offers a radically different
conception of living things, one that is not mechanistic or reductionist or
rooted in fixed entities or substance. Instead, it is emergent and holistic and
rooted in continual flux and change – what is now called dynamics. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Both process philosophy and enactivism have
always had some <a href="https://plato.stanford.edu/entries/embodied-cognition/">links to Buddhist philosophies</a>, which (I think at least) have
tainted them with an aura of mysticism and woo. That is unfair, as the Buddhist
philosophies in question can be separated from any aspects of spirituality or
religion (see here for a <a href="http://www.wiringthebrain.com/2019/01/genetics-is-karma-western-science-meets.html">relevant discussion</a> that I had the pleasure of taking
part in). But to many scientists, the ideas of process philosophy (if they have
heard of them at all) have remained too vague and nebulous to be considered
truly scientific or to give any kind of experimental purchase. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The new approaches described above will, I
hope, help to ground these philosophical approaches in experimental science,
making them rigorous and quantitative, and hopefully demonstrating their power
to help us, like Neo, see the meaningful patterns in <a href="https://en.wikipedia.org/wiki/The_Matrix">the Matrix</a>. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">*thanks to Jag Bhalla for the reference and
many other helpful suggestions</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"><br /></span></div>
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-->Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0tag:blogger.com,1999:blog-6146376483374589779.post-42079626020839884062019-07-14T02:38:00.001-07:002019-07-14T02:38:18.592-07:00The murderous brain - can neuroimaging really distinguish murderers?<div dir="ltr" style="text-align: left;" trbidi="on">
<br />
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB"></span></b><span lang="EN-GB"></span><span lang="EN-GB">A new study claims that neuroimaging can be
used to distinguish the brains of murderers from non-murderers. It follows in a
long tradition of attempts to find biological indicators of violent criminality,
from faces to skull bumps to genes to brains. But are the data convincing? Does
this study really accomplish what it claims? Is it even based on a well-founded
question? And what are the ethical implications? </span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Here is the abstract of the <a href="https://www.ncbi.nlm.nih.gov/pubmed/31278652">paper</a>, by Ashly
Sajous-Turner and colleagues:</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;">Homicide is a significant societal
problem with economic costs in the billions of dollars annually and
incalculable emotionaimpact on victims and society. Despite this high burden,
we know very little about the neuroscience of individuals who commit homicide.
Here we examine brain gray matter differences in incarcerated adult males who
have committed homicide (n = 203) compared to other non-homicide offenders (n =
605; total n = 808). Homicide offenders’ show reduced gray matter in brain
areas critical for behavioral control and social cognition compared with
subsets of other violent and non-violent offenders. This demonstrates, for the
first time, that unique brain abnormalities may distinguish offenders who kill
from other serious violent offenders and non-violent antisocial individuals.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Let’s first think about the reasoning
behind the study, which is encapsulated in the clause: “we know very little about
the neuroscience of individuals who commit homicide”. There is not much more
detail given in the paper itself as to the motivation for the study, but this
clause is rather revealing of a number of underlying assumptions: </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -.25in;">
<span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">1.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Murderousness is something that
there is “a neuroscience of”. </span></div>
<div class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;">
<span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">2.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">There is, moreover, something in
common in the brains of murderers – some shared difference that can distinguish
them <i style="mso-bidi-font-style: normal;">as a group</i> from
non-murderers.<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;">
<span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">3.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Structural neuroimaging is a
good way to detect such a difference – that is, it should manifest in the <i style="mso-bidi-font-style: normal;">volume</i> of some brain regions. </span></div>
<div class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -.25in;">
<span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">4.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Identifying such brain regions
will tell us something about the biology of violence.</span></div>
<div class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -.25in;">
<span lang="EN-GB" style="mso-bidi-font-family: Cambria; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: Cambria; mso-fareast-theme-font: minor-latin;"><span style="mso-list: Ignore;">5.<span style="font: 7.0pt "Times New Roman";">
</span></span></span><span lang="EN-GB">Identifying the pattern of
brain differences will allow us to distinguish murderers from non-murderers. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, the unstated hypothesis is that
murderers differ biologically from non-murderers, and that we can discover the
murderous essence by looking at the size of bits of the brain. In addition, it
is implied that it would be a good thing if we could do that. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Would it be a good thing? Good for whom? As
mentioned above, many people have tried to find some kind of biological marker
to distinguish those inclined to violence and especially to murder. In the
1800’s, phrenology was looked to as a way of telling who was bad and who was
mad. </span><span lang="EN-GB" style="mso-fareast-font-family: "Times New Roman";">As
described in this <a href="http://theconversation.com/natural-born-killers-brain-shape-behaviour-and-the-history-of-phrenology-27518">excellent piece</a> by James Bradley: “Two ideas lay at the heart
of phrenology’s seductive power. First, different areas of the brain were
associated with different mental capacities or faculties. And, as the brain
developed, it shaped the skull.”<span style="mso-spacerun: yes;"> </span>That
meant that the detailed landscape of bumps and depressions on a person’s skull
gave a window to their personality, including possibly murderous instincts. </span><span lang="EN-GB"></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br /></span></div>
<div class="MsoNormal">
<span lang="EN-GB">Francis Galton, the father of eugenics,
looked to physiognomy for markers of criminality, painstakingly creating
<a href="https://en.wikipedia.org/wiki/Composite_portrait">composite photographs</a> of the faces of criminals and comparing them to
upstanding members of Victorian society.
This tradition has been recently revived with the brute force of machine
learning, in a <a href="https://www.technologyreview.com/s/602955/neural-network-learns-to-identify-criminals-by-their-faces/">study in China</a> claiming to be able to discriminate criminals
from law-abiding citizens based on pictures of their faces. (<a href="https://callingbullshit.org/case_studies/case_study_criminal_machine_learning.html">Additional analyses</a> suggest a bias in the collection of photos that may be
driving the effect).<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://www.dnalc.org/view/12125-Composite-portraits-showing-features-common-among-men-convicted-of-crimes-of-violence-by-Francis-Galton-with-original-photographs.html"><img alt="https://www.dnalc.org/view/12125-Composite-portraits-showing-features-common-among-men-convicted-of-crimes-of-violence-by-Francis-Galton-with-original-photographs.html" border="0" data-original-height="710" data-original-width="491" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8ytt_MNHmoIDQm1FpChx8g4TZCDVNB5H84uEPlR_JidxgYMSy0J0y3Y7hp9eRudrbBvPHdGrhvvyJAVtlX4vLx12_Jty1Xqah5zExH8wjtLYxVkFJnsKl3qCj3olYiR12cfXu2xHWhV1z/s640/Galton-criminal+faces.png" width="442" /></a></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Genetic variants have also been <a href="https://pdfs.semanticscholar.org/57e3/f3ecc67be0ee43bf7348ed6b230e392b4d5b.pdf">invoked</a> as
underpinning a murderous instinct in some people. The most famous of these is
the gene encoding monoamine oxidase-A, or MAOA, an enzyme involved in serotonin
metabolism. Serious mutations in this gene are indeed associated with a drastic
increase in violent criminality. Fortunately, such mutations are extremely
rare. Unfortunately, the idea was extended to a very common variation in the
same gene, which was associated with all kinds of behavioral outcomes in
candidate gene analyses, which have subsequently been <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959575/">shown to be spurious</a>.
This hasn’t stopped the idea of the “warrior gene” from taking hold in the
public consciousness, however, nor has it prevented information on a
defendant’s MAOA common genotype being <a href="http://www.bbc.com/future/story/20180530-the-controversial-debut-of-genes-in-criminal-cases">used in court</a>. <span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
premise</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">All of these approaches assume that
murderers differ biologically from non-murderers (in a way that at least partly
explains their murderousness). Is there any reason to think this is the case? Well,
yes, there is. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">First of all, the vast majority of murderers
are men. <a href="https://www.un-ilibrary.org/drugs-crime-and-terrorism/global-study-on-homicide-2013_c1241a80-en">Worldwide</a>, 96% of homicides are committed by men (and 78% of the
victims are male). There is lots of <a href="https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005416">evidence from other species</a> that suggests
this reflects an innate difference in physical aggressiveness between the sexes,
with an underlying neural basis. So, yes, it seems some brains may be more
murdery than others. This at least establishes the principle that there could
be something biologically different between individuals (in addition to sex) that
influences likelihood to commit homicide. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">That idea is further supported by twin and
adoption studies showing that antisocial behaviour, physical aggression,
arrest, and incarceration for violent crimes are all <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3856338/">partly heritable</a>. That is,
being genetically related to someone with high levels of such behaviors makes
it more likely that a person will also show such behaviors. This effect is
additional to the significant effects of growing up in the same household with
people showing such behaviors. (For those keeping score, genetic effects (i.e.,
the heritability) tend to explain ~30-40% of the variance and the effect of the
shared environment tends to be about the same). </span></div>
<span lang="EN-GB"> </span><div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, okay, it’s not crazy to think that some
biological factors affecting an individual’s psychological make-up make a contribution
to likelihood to commit homicide. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">But is there any reason to think that
murderers would differ in <i style="mso-bidi-font-style: normal;">one particular
way</i>? The group comparison design of the study implies this hypothesis. But
if the <a href="https://en.wikipedia.org/wiki/Anna_Karenina">Anna Karenina</a> model applies – “happy families are all alike; every
unhappy family is unhappy in its own way” – then there may be little in common
between the biological factors making one person murderous versus those at play
in another. If each murderer were unhappy in his own way (biologically speaking),
you would never detect that in a group average comparison. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">What might such biological factors be? What
psychological traits might increase one’s likelihood to commit homicide? (Whether
one actually does or not would be hugely context-dependent, but let’s continue
with the idea that some people may be innately more murderous than others, in
general). You could imagine any or all of the following traits might be
involved: impulsivity, mood stability, aggressiveness, threat sensitivity,
punishment sensitivity, intelligence, executive function, vengefulness, agreeableness,
jealousness, honesty, narcissism, psychopathy, empathy, moral reasoning,
general meanness, sensitivity to alcohol or drugs, and on and on. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, you could have one murderer with high threat
sensitivity, impulsivity, and aggressiveness under the influence of alcohol,
and another with high narcissism and psychopathy and deficient moral reasoning.
If you took a hundred murderers, you might have a hundred different profiles.
This rather undermines the design of the experiment from the get-go. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
design of the experiment</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The next implicit assumption in the
experimental design – that differences in such traits should be manifest in the
size of various brain regions – is also not well justified. Why would we expect
that to be the case? Is that how psychological traits are determined? By the
relative <i style="mso-bidi-font-style: normal;">size</i> of bits of the brain? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This is just the modern, neuroimaging “<a href="https://www.ncbi.nlm.nih.gov/pubmed/21856431">blobology</a>” version
of phrenology. The reasoning behind this seems to be: brain region X is “involved
in” Y (or, in even worse wording, “does” Y). Therefore, if brain region X is
bigger, a person will be better at Y. </span></div>
<div class="MsoNormal">
<span lang="EN-GB"> </span></div>
<div class="MsoNormal">
<span lang="EN-GB">It’s 2019 – is this really how we
understand the relationship between the complex functions of the mind and the
neural substrates that carry them out? Just based on the real estate occupied
by supposed functional modules? Can we actually map complex cognitive functions
to little bits of the brain? And is bigger better?</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This paper is not unusual in adopting this
logic – it is a vague and unquestioned starting position for many similar
studies. The literature is chock-full of reports of such correlations – that
is, in fact, the main methodology of a lot of what can be called “psychology,
with added neuroimaging”. But to the best of my knowledge, despite thousands of
claims, there are few robust, well-replicated examples correlating the size of
little bits of the brain with variation in psychological traits. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">There are, in fact, all kinds of parameters
that could vary that would affect the function or tuning of a circuit (involving
many, distributed regions) that would not be visible by structural
neuroimaging: variation in levels of neurotransmitter receptors, or
distribution of specific types of interneurons, or altered density of dendritic
spines, or differences in many other aspects of synaptic microarchitecture, or
neurochemistry, or connectivity, etc. Size isn’t everything. In fact, we have
little reason to think it’s anything. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, the experimental design is not, in my
view, well founded. As is quite common, the implicit assumptions underlying it
go completely unexamined in the paper (and presumably unchallenged by the reviewers
or the editor).</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"><b>The methodology </b></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Now, what about the methodology and the
findings? Clearly, they found something, otherwise we wouldn’t have heard about
it. (This is not a trivial statement – the general existence of publication
bias bears directly on how much weight we should put in the “positive” results,
especially if a study was not <a href="https://www.psychologicalscience.org/observer/preregistration-becoming-the-norm-in-psychological-science">pre-registered</a>). </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">On the plus side, the sample is very large
and has a good control group: 203 convicted murderers compared with 605 people
convicted of other crimes, all from the same male prison population, all
scanned under the same conditions on the same scanner (as far as I can tell). The
control group was further broken down into violent and non-violent offenders. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The hypothesis being tested – or maybe we
should say the idea being explored – is that the brains of murderers would show
some structural differences to the brains of non-murderers. More particularly,
the researchers stated:</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;">We hypothesize that homicide offenders
will have deficits in areas of executive functioning and limbic control areas
within the prefrontal cortex and anterior temporal cortex compared to
non-homicide offenders.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">They didn’t actually specifically test that
hypothesis, however. Instead, the analyses performed were highly exploratory,
looking for effects in any direction, anywhere in the brain. To do that, the
researchers use a method known as <a href="https://en.wikipedia.org/wiki/Voxel-based_morphometry">voxel-based morphometry</a> to look for
differences in size of bits of the brain. Basically, this takes the scan of an
individual’s brain and warps it into a common template space to allow averaging
and comparison across groups. The amount of warping that is required to get the
individual’s scan into the template is recorded on a voxel-by-voxel basis and
that is taken as an estimate of the amount of grey matter in that bit of the
brain in that individual, relative to everyone else. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The next step is to average out those
values in the common template for each group and compare them. That raises a
statistical problem, given that you are performing tests on over a million 1mm<sup>3</sup>
voxels in the brain. Various statistical methods can be used to correct for
these multiple comparisons. Here, the authors used the <a href="https://en.wikipedia.org/wiki/False_discovery_rate">False Discovery Rate</a>. In
addition, a number of possible confounding factors that differed between the
groups were included in the analysis of variance (ANOVA) model, as listed below.
(PCLR refers to a test for <a href="https://en.wikipedia.org/wiki/Psychopathy">psychopathy</a>). The idea is that controlling for these
factors in the ANOVA gives you confidence that any differences observed are not
just driven by that factor, making it more likely that they are driven by the
factor of interest – murder. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;">One way ANOVA was performed on a
voxel-by-voxel basis over the whole brain using SPM12 to evaluate differences
in regional gray matter volumes between Homicide (n = 203), Violent
Non-Homicide (n = 475) and Minimally Violent (n =130) offenders, with all three
groups included as factors in each analysis. The ANOVA model included each
subject<b>’</b>s total brain volume (i.e., gray matter plus white matter), PCLR
total scores, substance use severity, age at time of scan, IQ, and time in
prison variables as covariates. Whole brain analyses using the False Discovery
Rate for control over Type I error, were performed for all comparisons.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">With that methodology in mind, let’s look
at the findings.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The
murdery bits</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The authors found dozens of clusters of
voxels (location information is given for 47) showing a difference in grey
matter volume between murderers and non-murderers. All of the differences were
a relative reduction in volume in the murderers. A comparison of murderers to
the subset of violent non-homicide offenders gave largely similar results while
</span><span style="color: #131413; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">comparisons between the control subsets, violent (non-homicide)</span>
<span style="color: #131413; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">and minimally violent offenders, “yielded mostly</span> <span style="color: #131413; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">null results, and no results survived correction for</span> <span style="color: #131413; mso-ansi-language: EN-US; mso-bidi-font-family: "Times New Roman";">multiple comparisons”.</span><span lang="EN-GB"></span></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0UqVf4npvoiEafFSLByeUuL8j6A5KFUEVkFqufgYg-PhlVsHSaeuTanR21EvkO1I0hqBA4pUO_jVcsIhFTp6jCaVEcUGz0RjgXTE4vZl-YYwk8yUeAF_G2lBzxLPwvLBIkR-lywdL_FKI/s1600/Screen+Shot+2019-07-12+at+9.08.24+AM.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1284" data-original-width="994" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0UqVf4npvoiEafFSLByeUuL8j6A5KFUEVkFqufgYg-PhlVsHSaeuTanR21EvkO1I0hqBA4pUO_jVcsIhFTp6jCaVEcUGz0RjgXTE4vZl-YYwk8yUeAF_G2lBzxLPwvLBIkR-lywdL_FKI/s640/Screen+Shot+2019-07-12+at+9.08.24+AM.png" width="494" /></a></div>
<br />
<div class="MsoNormal">
<span lang="EN-GB">So, what are we to make of these findings?
The first question is: should we trust that they are “real” and not a
statistical blip? The answer is very difficult to discern. The statistics have
all been done in the standard way for this kind of study, but is that standard
actually rigorous enough?</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The typical approach is to let the software
do the statistical jiggery-pokery, and if some difference comes out as
significant, then it’s taken to be real. I find that a little unconvincing, and
the reason is empirical: the literature is full of studies performing exactly
these kinds of analyses on neuroimaging data – using FDR and controlling for
all kinds of confounds – and claiming some significant differences between
groups, only for them to fail to replicate in subsequent studies. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">At some point, you have to ask if the
stats are doing what we think they’re doing. There is, in fact, some <a href="https://www.ncbi.nlm.nih.gov/pubmed/19944173">debate</a>
about whether the FDR is an appropriate measure and how it should be
implemented – by voxels, or by clusters of a certain size, for example. </span><span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;"></span><span style="mso-spacerun: yes;"></span><span lang="EN-GB">In
addition, there is considerable doubt as to the possibility of effectively
“<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152719">controlling for</a>” possible confounding variables that differ between the
subgroups.
Some <a href="https://statmodeling.stat.columbia.edu/2019/01/25/regression-matching-weighting-whatever-dont-say-control-say-adjust/">claim</a> that “control for” should really read: “attempt to adjust for using
unrealistic linear assumptions”<span style="mso-spacerun: yes;"></span>, while others argue it is flat out
<a href="https://scholar.google.com/scholar?cluster=2573923488827590810&hl=en&as_sdt=0,26">impossible</a> to correct for confounds, using ANCOVA.
</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">You would like your stats to give you an
indication of how robust and generalizable a finding is – that isn’t actually
what they do, but it is implicitly how they are (mis)interpreted. In this case,
for example, the authors claim to have discovered something about “murderers”,
that is, murderers in general, not just about the murderers in their sample. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">But the best way to see if your findings
are robust and generalizable is to directly test whether they replicate in a
separate sample. For this kind of population, this is obviously a tall order,
and it is understandable that the authors were not able to accomplish it. However,
without such replication, and with the caveats about the statistical
methodology, it is hard to know how much trust to place in the findings. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Interpreting
the findings</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Taking them at face value, the authors focus on prominent differences
in areas of the cingulate cortex, insula, prefrontal cortex, and orbitofrontal
cortex. These structures are implicated in many aspects of behavioral control
that could be seen as relevant to “murderousness” (emotional regulation,
impulse control, weighing possible negative consequences of an action, and
others). However, differences also appear in many other parts of the brain,
including for example, the somatosensory, auditory, and visual cortices, and
the cerebellum, which are less obviously implicated in the kinds of cognitive
tasks we might expect to be involved. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"><a href="https://www.theguardian.com/science/2013/may/12/how-to-spot-a-murderers-brain">Prior work</a> has also reported some
differences between the brains of violent criminals or psychopaths and controls
and the authors point to some overlap in the brain regions where such
differences have been found, as well as some variation. This raises an
interesting question as to how we should assess whether an imaging finding
replicates. Should we expect the same cluster of voxels to differ consistently
across different samples? (This may not even be comparable if the template
space is defined from the subjects in each sample). If we just see some
clusters differing in the same broad region, then, is that a replication? How
are we defining a “region”? If any clusters in any regions “replicate” should
we focus on those as consistent signal and ignore the others? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">The tendency of course, when faced with a
long list of findings, is to focus on the ones that make the most sense,
according to your prior knowledge (also known as your preconceived biases). The
same dynamic is seen in the analysis and discussion of results from genomics
approaches, such as <a href="https://en.wikipedia.org/wiki/Genome-wide_association_study">genome-wide association studies</a> or transcriptomics. Faced
with a list of hundreds of genes that their study has just “implicated”,
researchers tend to pick a few favorites and tell a story about them, while
ignoring the rest. The positive hits in your prior regions of interest can be
taken as supporting its involvement, but is that really how we should update
our hypotheses? By selectively attending to the evidence that confirms our
priors, while ignoring evidence implicating other regions? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">There is an additional problem inherent in
VBM analyses, which is that human brains are quite variable. Not just in
overall size or subtle variations in shape – people also show quite a bit of
variation in the layout and shape and size of various functional areas, defined
by which bits are active when we are doing various tasks or which bits tend to
be talking to each other. Our brains are so unique, in fact, that this
distribution of functional activations is referred to as a “<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=27600846">neural fingerprint</a>”. </span><span lang="EN-GB"> </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">So, when you do VBM, and you are warping
voxels from some little bit of the brain in one individual into a common space,
there is no guarantee that it belongs to a functionally homologous region in
another individual. It’s more likely to than not, perhaps, and an average map
can be made, but there will still be lots of idiosyncratic variability in the
layout, which makes assigning function to regions in the template more
challenging. Indeed, <a href="http://dx.plos.org/10.1371/journal.pbio.2007032">newer approaches</a> are defining these functional regions on
an individual basis first, before performing any kind of group averaging. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="http://dx.plos.org/10.1371/journal.pbio.2007032"><img alt="http://dx.plos.org/10.1371/journal.pbio.2007032" border="0" data-original-height="1150" data-original-width="1252" height="586" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjO2beE6ZD_9pH8DXe_pFgzP1N0De4VSVe3J6XMLJi7hHwPWUH3OLzhGDX6xwy9x4n9nxs3hSglT9EMvoMzz0um5d3VwB0MpuHVgLhfoD_isIAE6jXvFIYRJwVQJk4IamGI6cdBnYyrB_Gi/s640/Screen+Shot+2019-07-10+at+7.51.15+AM.png" width="640" /></a></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB"></span><span lang="EN-GB"></span><span lang="EN-GB">Finally, there is the issue of causality.
This kind of observational study can only provide a correlation. Taking the
findings at face value, a plausible interpretation is that the brain
differences <i style="mso-bidi-font-style: normal;">cause</i> the murderousness.
But it is certainly also conceivable that these differences arise as a <i style="mso-bidi-font-style: normal;">consequence</i> of traumatic and violent
experiences, which people who eventually became murderers are likely to have gone
through. Or maybe they’re due to some other <i style="mso-bidi-font-style: normal;">confound</i>
that was not fully corrected for or not anticipated at all. Who knows? Maybe
they’re a marker of guilt and remorse.</span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">To sum up, we have the observation of a
profile of differences across many regions between the brains of murderers and
non-murderers in this sample. There are, I think, legitimate questions about
the statistical robustness of the findings in the first instance. There is also
a question as to whether, if they are “real” and not just statistical blips,
they are really driven by the factor on which the groups were chosen (murder) and not by some known or unknown confounding variable. Finally, even if they are taken
at face value, it is hard to know what the overall profile means or whether it
really tells us anything about the (varied) psychology of murderers that we
didn’t know before. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">Practical
implications</span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Research like this has real-world impacts,
whether or not they are intended by the authors or warranted by the strength of
the data. You can bet that reports of these findings will increase the use of
brain scans as supposedly exculpatory evidence in murder trials. This practice
is already happening, based on previous reports of a similar nature, and has
been seen for genetic findings as well, despite the fact that the associations
have been shown to be spurious. Both types of evidence <a href="https://academic.oup.com/jlb/article/2/3/485/1918085">have proven effective</a> in
getting sentences reduced, on the basis that the defendant is biologically
predisposed to violence and thus cannot be held fully responsible for it.<span style="mso-spacerun: yes;"> </span></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">But the flip side of this appeal to
biological essentialism is that such a person may be deemed less likely to be
rehabilitated and more prone to recidivism. Indeed, you could see prosecutors
or parole boards using the same evidence to argue, on a different basis, for
longer sentences. Estimating the likelihood of future criminality or violence
is, of course, a normal part of such decisions – the question is whether a
brain scan of an individual can actually give you any accurate or helpful
information in that regard. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">And the answer is no. Group average differences do not necessarily allow prediction of individuals and the question is untested in this study.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">In fairness, the authors discuss this
explicitly:</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;">While this report demonstrates aggregate
differences between homicide offenders and other violent offenders that are
highly statistically significant, this should not be mistaken for the ability
to identify individual homicide offenders using brain data alone, nor should
this work be interpreted as predicting future homicidal behavior.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">However, that caveat is quarantined to the
final section of the paper on “Limitations and future directions”. Having such
a section is absolutely standard practice and certainly a good one, as it is
used to explicitly lay out limitations of the experimental design and
alternative interpretations of the data. But the practice of corralling those
concerns into one section, and presenting them as an afterthought, frees
authors to blithely ignore them in the way they present and interpret their
findings in the rest of the paper. If challenged, they can always point to the
final section to show how rigorous and objective they have actually been and
how up-front and circumspect about possible weaknesses of their claims. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">If you were cynical, you might call it the
“covering your ass” section. Having it there <a href="https://www.lesswrong.com/posts/oMYeJrQmCeoY5sEzg/hedge-drift-and-advanced-motte-and-bailey">gives licence</a> to make the boldest
claims in all the other sections of the paper, especially the title and the
abstract, and, crucially, the press release.</span><span lang="EN-GB"> </span><span lang="EN-GB">In this case, the authors undermine their
own caveat by ending the abstract with this claim:</span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;">This demonstrates, for the first time,
that unique brain abnormalities may distinguish offenders who kill from other
serious violent offenders and non-violent antisocial individuals.</span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">They may argue that this sentence is
intended to mean just that there are aggregate, group average differences
between murderers and non-murderers in their sample. But a reasonable person is
likely to read the word “distinguish” as implying that these “unique brain
abnormalities” can, literally, be used to distinguish <i style="mso-bidi-font-style: normal;">individual</i> murderers from <i style="mso-bidi-font-style: normal;">individual</i>
non-murderers.</span><span lang="EN-GB"> </span><span lang="EN-GB">Similarly loose language is used in this
<a href="https://twitter.com/Decety/status/1148229983577546752">tweet</a> by Jean Decety, one of the senior authors of the paper:</span>
</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">“</span><span lang="EN-GB" style="mso-bidi-font-family: "Times New Roman"; mso-fareast-font-family: "Times New Roman";">Our study, which
includes 808 incarcerated males, demonstrates unique brain abnormality (in
ventromedial prefrontal cortex and insula) that differentiate offenders who
killed from other violent offenders”</span><span lang="EN-GB"></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">That sounds pretty definitive. The
differences are apparently unique to murderers (though this hasn’t been shown - indeed, the paper itself states that "the localized deficits in gray matter exhibited in this sample of homicide offenders are not necessarily specific to homicidal behavior") and
also highly specific to just a couple brain regions (though the data also do not
show that). If I’m a defense lawyer I may go looking for
someone to scan my defendant’s brain and tell me they show evidence of this
“unique brain abnormality”. If I’m on a parole board, I might be similarly
interested. Indeed, why wait until someone has committed a murder to use such
data to predict future crime? Why not get in there first and identify
“high-risk” individuals? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">This may seem far-fetched for brain scans,
as it’s highly impractical, but just wait until genome-wide association studies
find some hits for criminality and see how easy it will be to generate a
<a href="https://en.wikipedia.org/wiki/Polygenic_score">polygenic score</a> that supposedly <a href="https://www.ncbi.nlm.nih.gov/pubmed/29513605">predicts this trait</a> for individuals. </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Whether the authors intend it or not, this
study feeds into a narrative of biological essentialism that conveniently lets
us ignore all the messy social factors and complex individual experiences that
may lead a person to commit murder. If we can track some objective indicator of
a biological risk of this behavior and supposedly put a number on it, you can
be sure that that number will be applied to individuals and used in all kinds
of unexpected ways, whether or not it has any actual validity. </span></div>
<div class="MsoNormal">
<span lang="EN-GB"> </span><span lang="EN-GB"></span><span style="color: #131413; font-family: "Times New Roman"; font-size: 10.0pt; mso-ansi-language: EN-US;"> </span>
</div>
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Kevin Mitchellhttp://www.blogger.com/profile/07172255754953214162noreply@blogger.com0