Early on in my reading and studying neuroscience I read about the glia, brain cells between the neurons. Not much was known about them at the time and they seem not to have been much studied. With my recent interest in polyviscosity I decided to check up on the glia.
Things have changed. Quite a bit is now known about them. They seem to be crucial. One recent article:
Robertson JM. The Gliocentric Brain. Int J Mol Sci. 2018 Oct 5;19(10):3033. doi: 10.3390/ijms19103033. PMID: 30301132; PMCID: PMC6212929.
Abstract: The Neuron Doctrine, the cornerstone of research on normal and abnormal brain functions for over a century, has failed to discern the basis of complex cognitive functions. The location and mechanisms of memory storage and recall, consciousness, and learning, remain enigmatic. The purpose of this article is to critically review the Neuron Doctrine in light of empirical data over the past three decades. Similarly, the central role of the synapse and associated neural networks, as well as ancillary hypotheses, such as gamma synchrony and cortical minicolumns, are critically examined. It is concluded that each is fundamentally flawed and that, over the past three decades, the study of non-neuronal cells, particularly astrocytes, has shown that virtually all functions ascribed to neurons are largely the result of direct or indirect actions of glia continuously interacting with neurons and neural networks. Recognition of non-neural cells in higher brain functions is extremely important. The strict adherence of purely neurocentric ideas, deeply ingrained in the great majority of neuroscientists, remains a detriment to understanding normal and abnormal brain functions. By broadening brain information processing beyond neurons, progress in understanding higher level brain functions, as well as neurodegenerative and neurodevelopmental disorders, will progress beyond the impasse that has been evident for decades.
I take it, then, that the glia are central to consciousness, reorganization, and polyviscosity. And that’s only one article.
It seems to me that one effect of the computational view of neural function has been implicitly to encourage treating networks of neurons as passive switching networks that just happen to be constituted of living cells. But the fact that cells are living has been treated as contingent and not essential to their switching functions. A great deal of neuroscience and cognitive reads like this and AI even more so. For that matter, that’s more or less how I thought about matters for years. That had begun to change by September of 2014 when I wrote a post, What’s it mean, minds are built from the inside? Here’s three paragraphs:
If we want a computer to hold vast intellectual resources at its command, it’s going to have to learn them, and learn them from the inside, just like we do. And we’re not going to know, in detail, how it does it, any more than we know, in detail, what goes on in one another’s minds.
How do we do it? It starts in utero. When neurons first differentiate they are, of course, living cells and further differentiation is determined in part by the neurons themselves. Each neuron “seeks” nutrients and generates outputs to that end. When we analyze neural activity we tend to treat it, and its activities, as components of a complicated circuit in service of the whole organism. But that’s not how neurons “see” the world. Each neuron is just trying to survive.
Think of ants in a colony or bees in a swarm. There may be some mysterious coherence to the whole, but that coherence is the result of each individual pursuing its own purposes, however limited those purposes may be. So it is with brains and neurons.
So, I’ve been moving away from the passive-switching-network view for a while.
But it took that 1988 paper by Fodor and Pylyshyn (pp. 34-45):
Classical theories are able to accommodate these sorts of considerations because they assume architectures in which there is a functional distinction between memory and program. In a system such as a Turing machine, where the length of the tape is not fixed in advance, changes in the amount of available memory can be affected without changing the computational structure of the machine; viz by making more tape available. By contrast, in a finite state automaton or a Connectionist machine, adding to the memory (e.g. by adding units to a network) alters the connectivity relations among nodes and thus does affect the machine’s computational structure. Connectionist cognitive architectures cannot, by their very nature, support an expandable memory, so they cannot support productive cognitive capacities. The long and short is that if productivity arguments are sound, then they show that the architecture of the mind can’t be Connectionist. Connectionists have, by and large, acknowledged this; so they are forced to reject productivity arguments.
Jerry A. Fodor; Zenon W. Pylyshyn (1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28(1-2), 0–71. doi:10.1016/0010-0277(88)90031-5.
THAT focused my attention on the problem of memory as a physical process. And that, in turn, led me back to Walter Freeman, which I discuss in this post, Physical constraints on computing, process and memory, Part 1 [LeCun]. And that in turn let me to my thoughts about polyviscosity – though I’d initially used the term “hyperviscosity,” but have abandoned it because it is already in use.
So, memory presents a physical problem (Fodor and Pylyshyn). That problem thus requires a physical solution: polyviscosity. And polyviscosity, it would seem, requires living tissue. Perhaps we’ll figure out how to implement it in inanimate materials, but at the moment living tissue is what we’ve got. And glial cells are central to the mechanisms of polyviscosity.
I’m tempted to say something like – and here I’m rambling again – that the glia implement consciousness. And the function of consciousness is to ‘operate’ the neuromolecular mechanisms of reorganization. And if that seems a bit circular, well, that’s the best I can do at the moment. The important point is that consciousness, reorganization, polyviscosity, and the glia and involved in the same phenomena.
More later.
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Earlier posts in this series:
- Consciousness, reorganization and polyviscosity, Part 1: The link to Powers
- Consciousness, reorganization and polyviscosity, Part 2: ‘Fluidity’ & its requirements
- Consciousness, reorganization and polyviscosity, Part 3: Substrate independence, NOT
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