The Holy Trinity of Cognitive Science
Endless banter about neuro-plasticity and myelination
(while fascinating) is saying nothing about how the
underlying system is “calculating”. You’re effectively
“describing” the weather to me but not telling me how
it works.
A jocular, irreverent and unashamedly lay-person collection of musings…
In the milieu and great sea of scientific endeavour on the human mind and cognition, while it might not be obvious on the surface, there are 3 great figures in modern times, who share some crucial distinctions.
They also have critically important and very weighty comment about scientific understanding, in each of their respective disciplines and with human cognition more broadly.
We’d do well to take note and reacquaint ourselves, as the tidal waves of shallow, trendy, more recent “pet theories” drown out these voices of reason altogether. (More on this further down).
Something noteworthy from the outset. Science isn't democratic. One person one vote doesn’t prove scientific explanation. It’s not a popularity contest.
Just because a theory has the weight of widespread opinion, at a given point in time, has nothing to do necessarily with whether that theory represents a viable “causal statement”. In fact many of the greatest discoveries in modern science, were all spurned and ridiculed at their inception and beyond.
3 Great Figures
I suspect I can hear already the hue and cry as I advance this. Because it will be so foreign to the typical self-made, contemporary science grad or post grad in the field and/or related disciplines.
In fact as I read and observe (to my limited capability) sometimes even senior faculty in various institutions, I’m perplexed at how uninformed discussions sometimes seem. And further, I note how much wheel spinning and breathless rhetoric goes on with matters that have often been exhaustively discussed already, (and in some cases resolved), many decades prior.
Ecclesiastes is right, “there is no new thing under the sun”. Almost.
So here are my 3 nominations;
God the Father
Within this trio, one figure stands out particularly. One body of work towers over the rest and in fact casts its shadows far afield into almost all related areas including Biology, Psychology, Philosophy and all matters Human Cognition.
It’s entirely without arrogance or hubris. It’s simply a product of the sheer breadth and depth of enquiry and the breakthrough ideas that were developed, which literally transformed whole fields of scientific endeavour.
I nominate Noam Chomsky as God the Father. (Of course he would never accept or allow this, so let’s just pretend…).
From the mid 50’s when Chomsky’s original theories on syntax and universal grammar burst onto the scene, science would never be the same. (Thank God).
The novel enquiry of “how does an infant, placed in a blooming buzzing confusion-(the human experience channelling William James)-even begin to pick out information that’s language related?”, was a long overdue question whose time had come.
From this through to “poverty of the stimulus”, the ubiquitous fact that in all cases of growth and development in biology and cognition, there is an enormous gap between the data available (stimulus), and the state of growth attained.
And finally, the generative procedure behind human language and perhaps even thought itself ,(which when pondered is nothing short of a miracle), and which very suddenly emerged in evolutionary history, pretty much perfectly formed like a “snowflake” in the mind, and which eventually came to define our species more than any other trait, separating us entirely from the rest of the organic world.
These (and so many more) are radical, deep and weighty notions, shrouded in some mystery and to an extent, even today they lie at the outer reaches of scientific understanding. To the extent that there is coherent understanding at all, humanity owes quite a debt to Chomsky and those working in the field he created.
Randy Gallistel
Gallistel’s work is also nothing short of mind-bending particularly for a science amateur (like myself).
Computational brain and mind theory is fine but a code effectively made up of ones and zeros that stores all memory somewhere in the brain (probably at a molecular level) is something I need a lot lot more time to get my head around.
Gallistel is pushing and challenging the limits of cognitive science, to define the physical basis for memory. The illusive engram so-called.
I’ll say more on this below, but if you looked at your phone today, or punched even a single key stroke on your lappy or tablet, you just made the Holy Trinity even more relevant. You just used and proved what Gallistel’s talking about.
The core concept of computational process, whether in the human brain or insect navigation, or a circuit of some kind, looms large here. (Also more on this below).
Since memory is invisible and ever present, perhaps this makes Gallistel the Holy Spirit.
David Marr
Sadly, Marr was taken before his time.
His seminal book “Vision” revolutionized the study and understanding of the human visual system and ultimately, computer vision.
Remarkable considering Marr was a Neuroscientist not strictly a Biologist.
Marr proposed 3 levels of analysis for vision as a system and this is key;
1)????Computational Level: What computations does the system perform and why?
2)????Algorithmic Level: What algorithm, what representations and procedures are used in the neural computation?
3)????Implementation Level: What are the physiological mechanisms (hardware) that implement these representations and carry out these algorithms?
That the information processing sequence with human vision is actually an algorithm and that it can be defined, demonstrated and understood, is also mind-bending.
Given the many references to vision within the life and times of Jesus, tenuously, we might nominate Marr for that role in the trinity.
Same Wavelength
Our trio of luminaries have some crucial ideas in common. They’re on the same wavelength. Within each of their respective fields of enquiry, more or less independently, they reached and maintained similar conclusions on foundational topics.
Computational Brain
Notions of internal computation are at the core of each domain here. Computational brain and mind theory can be jarring at first encounter but on reflection it doesn’t have to be too painful.
For those who balk at the idea of the brain being anything like a computer, firstly substitute the word “computation” with evaluation, figuring, estimation or best of all “calculation”. Another way of stating it could be “rule-based calculation”. Secondly, that the brain is doing something along these lines is incontrovertible. It’s a structured, rule-based calculation process, that yields a result either in Language or Vision or general function and Memory, at the simplest level.
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Causal Statement
In their domain, each of our actors are somewhat “possessed” with defining a causal statement that explains how the system works, not just describing what it’s doing on the surface.
That is to say with each topic of enquiry, a theory must be developed that plausibly explains the function and inner workings of the faculty.
This is an extraordinarily high bar.
Much of the contemporary discussion has reverted to shallow description (perfect Ted talk fare). Endless banter about neuro-plasticity and myelination (while fascinating) is saying nothing about how the underlying system is “calculating”. You’re effectively “describing” the weather to me but not telling me how it works.
Repudiation of Behaviourism
Here comes the deep water.
Behaviourism (the notion, in essence, that all behaviour/function is simply conditioning like a habit) is roundly rejected by the trinity, as a satisfactory explanation for how things actually work. (With good reason).
At the very least, to be fair, it should be noted that from inception, behaviourism completely rejects any underlying mechanism beyond conditioning. That is to say, from the outset it was intentionally disregarded. “Behavioural theory…says that only observable behaviour should be studied, as cognition, emotions, and mood are far too subjective”.
Given this it should come as no great surprise that it fails to offer a deeper causal explanation. Notwithstanding all this, the associationism and behaviourism camp, seem to have eternal life of their own and continue in relentless opposition to this very day.
Implications for Technology and Statistical Analysis
The cross over with modern computer science is not lost here. In fact in all 3 cases much of the research has paved the way for break-throughs in the tech field.
Chomsky’s studies on language have greatly assisted natural language processing, AI and computational cognitive sciences as have Gallistel’s with computer memory and Marr’s (as mentioned earlier) with what’s become known as computer vision.
However there’s a flip side.
As more and more of modern research effort moves to statistical analysis, the cautionary warnings from these surviving experts in the field are increasingly relevant.
Using AI and related technologies may well give better prediction than conventional scientific enquiry, but they have nothing to say about the underlying mechanisms i.e. how things actually work.
Put simply, taking the weather once again, yes, you can feed terabytes of ?data into a super computer, and by sheer brute force you’ll quite possibly get a better weather forecast than the Bureau, but you’ve made absolutely no scientific advance in explaining how the weather system actually works.
Worth keeping in mind that all of the major discoveries in modern science, going back to Galileo, have more or less agonized over defining a causal statement and providing an explanatory theory as opposed to settling for superficial description.
Certainly AI et al can and should be used, but we shouldn’t abandon old school science just yet…
Is it Midnight Yet?
While psychopathic world leaders knowingly “play chicken” with the prospect of terminal destruction via nuclear war (and demonstrate that actually the rest of humanity is not really that important, given we’re 100 seconds to midnight), you could do a lot worse than take a moment or 2 and contemplate these big ideas for yourself over a coffee or something...
It provides a welcome respite or at least brief distraction from the happenings of the outside world, especially on these freezing winter weekend afternoons.
I commend the reference/reading list below in case you’re so inclined…
Epilogue
It was never intended that this brief excursion would be so gender biased. It would seem to be a reflection as to how biased the sciences were historically, that our trinity are all Gents.
In a lame attempt to at least restore some kind of balance, please check out these very very honourable mentions in no particular order;
Elizabeth Spelke - https://psychology.fas.harvard.edu/people/elizabeth-s-spelke
Nancy Kanwisher - https://mcgovern.mit.edu/profile/nancy-kanwisher/
Barbara H. Partee - https://people.umass.edu/partee/
References - See for yourself ??
Chomsky:
https://www.linguisticsociety.org/sites/default/files/13_90.4Berent.pdf - Rich Languages from Poor Inputs
https://podcasts.apple.com/au/podcast/sbs-lecture-series-noam-chomsky/id502574321?i=110512186 – What is special about Language?
https://www.youtube.com/watch?v=yJp1-Od67-U – Language and the mind revisited
https://www.youtube.com/watch?v=Rgd8BnZ2-iw – After 60 Years, Generative Grammar
https://www.youtube.com/watch?v=cMscNuSUy0I – Lex Fridman (MIT) Language, Cognition, and Deep Learning
C. Randy Gallistel:
https://www.youtube.com/watch?v=D4Fbfs0MEBk – Where is the Engram?
https://www.ling.upenn.edu/~kroch/courses/lx400/Gallistel-King_chaps1-9.pdf - Memory and the Computational Brain
?David Marr:
https://mitpress.mit.edu/books/vision - Vision By David Marr
https://www.youtube.com/watch?v=qAuctNYGNm0 – Applying Marr’s 3 levels, Chomsky
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