Ken Miller @kendmiller@qoto.org

@strangetruther @achristensen56 @NicoleCRust @bwyble @DrYohanJohn @ekmiller

Nope, no relation. There's another Ken Miller scientist at Brown who's a cell or molecular biologist and a Catholic and writes books on science and religion. Also no relation. There's a lot of Millers in the world ...

@ekmiller @bwyble @strangetruther @achristensen56 @NicoleCRust @DrYohanJohn

Brad, re evidence of repeating columns outside V1: you see it in V2, MT, V4, IT. More generally, a sign of periodic organization of preferred features is the patchy arrangement of long-range (>1mm) horizontal projections, which in V1 are patchy because they're targeting other patches of similar preferred orientation. My memory of old anatomy papers on higher areas of monkey cortex are that, wherever you look in primate cortex, you see such patchiness of long-range connections. I've forgotten what papers those were though, quite possibly from Jenny Lund, or maybe Kathy Rockland, or someone else ...

@jiahongbo @bwyble @strangetruther @achristensen56 @NicoleCRust @DrYohanJohn

I'm sure orientation and ocular dominance do not begin to describe what V1 is doing. But they are two important and prominent things that V1 represents, and so a region that gives a complete local representation of them is likely to have a complete local representation of the visual scene.

@bwyble @strangetruther @achristensen56 @NicoleCRust @DrYohanJohn

Well, the question is, what is the level of the unit that you see repeated? The fact that individual neurons are repeated would not account for any of the specificity of the repeated architectures one sees across each of the four structures. Based on about a 1sq mm chunk of V1 containing all preferred orientations from both eyes at a given retinotopic position, with the next chunk over (e.g., about 1mm away) having half-overlapping receptive fields, Hubel and Wiesel suggested that size of chunk as a cortical processing unit (the size varies across species from 1/2 mm to 1.5 mm or so, but order of magnitude 1 mm). That is at least roughly consistent with dense connectivity in cortex extending horizontally maybe 200-300 microns from any given point, along with sparser connectivity over longer distances. Comparable structures have been seen in many other cortical areas. So that is what I think of as the unit that repeats. Others have focused on a 25 x 25 micron or so "minicolumn", or the area spanned by the neurons spawned from a given radial glial cell. That also repeats, but personally seems to me too small to be a computational unit, i.e. to do a self-contained computation.

But more generally, I'd want to characterize the repeated units of each of the four structures that are connected, that talk to one another -- a thalamo-cortical-basal-ganglia-cerebellar unit. I suspect the cortical part is something like Hubel & Wiesel's square mm, but maybe it would be more like a cortical area, I'm really not sure.

#neuroscience

@vanessabrown Thank you, very helpful --

@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

Does anyone have expertise in EMDR (eye movement desensitization and reprocessing) and how effective it is, as opposed to more standard approaches or other approaches, for trauma w/ flashbacks and related symptoms? Need info for a family member. Thank you.

#neuroscience #psychology

For neuro paper threads: sigmoid.social/about/more has already claimed #PaperThread and #NewPaper (the latter announcing a paper without a thread) for the AI community. I enjoy seeing their papers too, but we need a distinct tag for neuro papers. For a thread, somebody suggested a #TootSuite, and I had suggested a #MastoPiece, but maybe we want something simple like #NeuroPaperThread and #NeuroNewPaper? or mix and match, like #NeuroSuite for a thread and #NeuroPaper for a paper w/o a thread?? Decisions, decisions.

I nominate @NicoleCRust to be the hashtag czar. Decide for us Nicole! (And anyone else, weigh in to help inform our czar!) And from your lips, or at least typing fingers, to the Mastodon's ears ...

@toddhorowitz @LeonDLotter @phdstudents @academicchatter @neuroscience @cognition
@NicoleCRust
#neuroscience

@LeslieKay @NicoleCRust @cogneurophys

did you mean he advised jr colleagues *not* to sign it?

@dangillmor @LopezLinette still banned on Twitter

@jaanaru @jiahongbo @NicoleCRust @Neurograce @wandell @anilkseth @DrYohanJohn @PessoaBrain @ShahabBakht @jerlich @LeslieKay

Nicole, you started out asking about complexity measures of consciousness. Anyone interested in this has to absorb Scott Aaronson's critique of IIT: https://scottaaronson.blog/?p=1799
He shows that the IIT measure does not even come close to isolating what we think we mean when we separate the conscious from the unconscious. The punch line is:

"More generally, we can achieve pretty good information integration by hooking together logic gates according to any bipartite expander graph: that is, any graph with n vertices on each side, such that every k vertices on the left side are connected to at least min{(1+ε)k,n} vertices on the right side, for some constant ε>0. And it’s well-known how to create expander graphs whose degree (i.e., the number of edges incident to each vertex, or the number of wires coming out of each logic gate) is a constant, such as 3. One can do so either by plunking down edges at random, or (less trivially) by explicit constructions from algebra or combinatorics. And as indicated in the title of this post, I feel 100% confident in saying that the so-constructed expander graphs are not conscious! The brain might be an expander, but not every expander is a brain."

Tononi, to his credit or blame, is so committed to IIT that his response is yes, such an arrangement of logic gates is conscious. But I think that pretty much destroys any connection of what he calls consciousness to what the rest of us are referring to when we use that term.

I don't doubt that there is some sense in which conscious brains are functionally in more complex states than unconscious brains. And that it might be possible to characterize this difference in ways that are, say, clinically meaningful in identifying awareness in locked-in patients. I have no idea how effective any of the existing measures are at this, or how unique they are in being effective (if they are), or whether, if they do the job, they are about as simple as any criterion that could do the job can be. I don't even know if these questions have been asked. At any rate, these are practical issues.

But the idea that one proclaims a theory, writes down an expression for complexity and proclaims that is the alchemical formula for consciousness -- well, that's just silly. I think that completely misunderstands what a theory is.

I'll also add that I agree with several people above (@neurograce, @DrYohanJohn, probably others) that the "hard problem of consciousness" -- why do objective arrangements of matter create subjective experience -- is not a question science can answer. Science is a process of distilling out the objective, measurable, reproducible. It can tell us all about the structures of neural activity that enter consciousness and create its contents, the NCCs. Maybe when we understand this and get used to it the hard problem won't seem so interesting or bothersome. Maybe it will seem natural that *that* kind of neural activity enters conscious awareness. Maybe the mystery will seem to disappear. But all science can tell us about are the objective structures and their correlations with subjective experience. Not why cold dead matter organized intro energy-consuming, reproducing (living) entities can, in some cases, produce subjective awareness.

#neuroscience @cogneurophys

Apparently Twitter has removed the tweets announcing the new no-links-to-outside-social-media policy and musk has said they will only be forbidding users that exist purely to promote alternate sites. He's also put up polls asking if they should allow such users and whether he should continue as ceo, sounds like he's planning to quit. So sounds like Mastodon links won't be coming down after all.

Now I've heard of another one, movetodon

@LucillaPiccari no, just in case one's algorithm picks up some names that another's doesn't. But they're all similar and quite possibly will be identical.

@karchie Thanks. I think you worked with Bartlett, right? He and I were postdocs together at Caltech way back.

Since twitter is now banning having mastodon usernames in your bio, they won't be in bios much longer. So this is a good time to take a last sweep through your followers with fedifinder, debirdify, and twitodon, all of which will find your twitter follows that list mastodon usernames in their bio. You can then output a csv file that you can then import to add anyone you're currently missing (to import, go to 'edit profile', 'export and import', 'import', and be sure to click 'merge' so it will merge these lists with your existing follows rather than replacing your existing follows.
#Neuroscience