Wednesday, June 22, 2022

Some Post-Publication Thoughts on the RNA Primer [Design for a Mind]

I’m talking about:

Relational Nets Over Attractors, A Primer: Part 1, Design for a Mind,

While I’ve got some ideas about what might go into Part 2, some of which I’ve mentioned in a Coda to Part 1, I have no definite plans to go to work on it.

What I’ve been thinking about is the scope of the piece. It’s not the first time I’ve written seriously about the brain. I’ve got a good bit of material in my book on music, Beethoven’s Anvil, and in several articles. The most important of those, by far, is the one David Hays and I published in 1988, Principles and Development of Natural Intelligence. That article is about the whole brain, developing five principles and relating them to: behavior, computational principle, neuroanatomy, phylogeny, and ontogeny.

I bring that up three times in the primer. The first time is in the introduction, where I introduce Mirian Yevick’s work, which is the basis of our fourth principle (figural). Then I mention it in discussing language, the fifth principle (indexing). Finally I introduce the modal principle (first) while discussing types of minds in order to make that point that, while the primer is about the cortex, it does not assume that the cortex is somehow isolated or autonomous. On the contrary, activity in the cortex is affected by the whole brain, with the modal principle being the deepest example. For it is implemented in the reticular formation, which is the phylogenetically oldest part of the brain. And yet it affects, in a broad way, what areas of the cortex are active during any given stretch of time.

So, the paper implies the action of the whole brain, not just the cortex. What does the primer add to what Hays and I did in Principles? It provides a way of thinking about how the cortex implements highly differentiated cognitive processes and, in particular, natural language semantics. And natural language semantics is the lever through which the mind develops abstract concepts and elaborates on them over the long-haul of cultural evolution. That’s what’s new in the primer.

And that, it seems to me, “closes the space” on how the mind works, at least informally. The burden of working out how abstract concepts are developed will not, of course, fall directly on neural analysis. We’ll need other mechanisms for that. That’s why I introduced the relational network notation. That’s how we’re going to have to understand the mind’s construction of concepts. There is the logic inherent in the notation itself, and there are the implications of that logic for neurodynamics.

On the one hand we have global neurodynamics, something Freeman talked about. But then we have the local neurodynamics of the cortical neurofunctional areas (NFAs). I am assuming that the the dynamics of each NFA have a measure of autonomy from both global dynamics and from adjacent NFAs. Otherwise it makes no sense to select them as units for analysis. Sure, each cortical NFA receives inputs from other cortical NFAs and sends outputs to them (to and from subcortical NFAs as well). But the activity with an NFA is dominated by signals passed between neurons within it.

And then we have grand mal epileptic seizures, which often start locally in one hemisphere, but then engulf the entire brain. Local autonomy is lost. But then so is consciousness.

More later.

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