@DrYohanJohn @bwyble
The diversity of perspectives is quite fascinating, right?

A random list from team canonical:

https://pubmed.ncbi.nlm.nih.gov/30359606/

@kendmiller
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944655/

https://www.pnas.org/doi/full/10.1073/pnas.0908383106

https://www.pnas.org/doi/10.1073/pnas.2005417117

@achristensen56 @NicoleCRust @bwyble

In other words, there is a whole continuum between "columns are interchangeable" and "each cortical column is a unique snowflake". Systematic architectonic variation has been observed: the challenge now is for a few computational neuroscientists to imagine a few functional/computational stories for why it's there.

This is why I used the term "cortical spectrum": it's not giving up, any more than the EM spectrum requires giving up.

@DrYohanJohn @achristensen56 @NicoleCRust @bwyble

I wish I knew what "normative arguments" means!😁

@NicoleCRust @achristensen56 @DrYohanJohn agreed, I may have a fairly narrow view on what the CM model is and how it influences ideas.

The idea of repetitive functional units is certainly baked into back prop and convolution.

@strangetruther @achristensen56 @NicoleCRust @bwyble @DrYohanJohn

A simple argument for some sort of canonical cortical computation is: "cerebral cortex ... processes ... diverse tasks with what appears to be a remarkably uniform, primarily six-layer architecture, albeit with significant differences in details across species and cortical areas [1,2,3􏰩,4–10,11􏰩,12–14]. ... This has long suggested the idea that a piece of six-layer cortex with a surface area on the order of a square millimeter constitutes a fundamental cortical ‘processing unit’ [e.g. 16,17].The cortex varies in surface area by a factor of 10000 across a set of 37 mammalian species, while thickness (the distance across the layers) varies only by a factor of 10 over the same species [18], suggesting that the most salient evolutionary change in cortex has been enormous multiplication of the number of ‘units’ [e.g. 14]."
The last two references are:
14. Rakic P: Confusing cortical columns. Proc Natl Acad Sci U S A 2008, 105:12099-12100.
18. Hofman MA: On the evolution and geometry of the brain in mammals. Prog Neurobiol 1989, 32:137-158.

This is from the 1st paragraph of a Current Opinion review paper that I wrote that Nicole cited further up in the thread (https://pubmed.ncbi.nlm.nih.gov/26868041/)

More generally I think there are (at least) 4 mammalian (and, except for cortex, vertebrate) brain structures that each clearly have repeating architecture, and that -- at least as studied in primates -- communicate pretty intimately with one another: cortex, thalamus, basal ganglia, and cerebellum. They communicate with specificity, eg a given piece of cortex communicates with given thalamic nuclei and given regions of basal ganglia and cerebellum, which communicate with one another, e.g. Boston & Strick https://www.nature.com/articles/s41583-018-0002-7. These specific ctx/BG/cerebellum interactions cover at least posterior parietal through frontal cortex, and perhaps higher sensory cortices as well, i.e. they cover all sorts of cognitive processing, not just motor processing which is the traditional function assigned to BG and cerebellum. So it's not just the enormous multiplication of cortical "units" (with diversification, i.e. the spectrum Y.J. referred to) , but also the corresponding multiplication of their partner thalamic, basal ganglia, and cerebellar "units" that suggest some fundamental computional operation, albeit again with diversification.

You don't see this sort of thing in the brainstem. Different bespoke nuclei or other sorts of neural units each do different pieces of different computations. In contrast, the existence of these structures with repeated modular subunits with roughly repeating architectures (despite much variability and diversification), and with specific patterns of interconnections between their modules, as well as their enormous growth in numbers of modules at least in mammalian evolution, all just scream out that some sort of computational motif is being repeated (with variations on the repeated units, much as multiple copies of a gene provide a substrate for evolution into multiple variants -- and occasionally quite new structures). That wouldn't happen by accident.

Kenji Doya long ago postulated that cortex is for associative learning, BG for reinforcement learning, and cerebellum for error-correcting learning. That still sounds like a decent 0th-order take. And, I'll add my speculation, one function of thalamus -- not all that it is doing -- is to take any modality of information whatsoever and convert it into a language that cortex understands, using a roughly uniform architecture with roughly uniform biophysics across all these different modalities of information.

#neuroscience