So that's an interesting parallel. Says something about memory.

It's akin to how the saying goes, that when we argue, we need to reach the same wavelength where the other one is to reach an understanding.

In communication studies or sociology or linguistics or one of those fields, there's the idea that communication is about making pacts about meanings, and finding the common ground to understand and delimit the message.

In a sense, from that basing, one could argue that understanding can be seen as an act of harmonizing. I think there's something universal in it.

Yes, I fall more towards the camp that a lot of our cognitive models, built from times when we didn’t have the resolution of understanding we have of the capacity of even a single neuron, and before we knew how astrocytes played a role, suffer from being an abstraction describing an abstraction. They are not tethered in the dynamics of the molecules and cells that give rise to the behavior, but rather from an interpretation of observed behavior.

This paper from the field of chronobiogy is one I’d recommend that helpfully contrasts this:

https://www.sciencedirect.com/science/article/abs/pii/S00393...

>In circadian research, the models are not proposals regarding the basic architecture of circadian mechanisms; rather, they are used to better understand the functioning of a mechanism whose parts, operations, and organization already have been independently determined. In particular, circadian modelers probe how the mechanism’s organized parts and operations are orchestrated in real time to produce dynamic phenomena—what we have called dynamic mechanistic explanation.

And what you’re describing, the enactivist description of cognition, (and 4E cognition more broadly as a framework), is one way the neuroscience community is trying to move past these issues.

Few things that give me confidence these are the right track:

1. Circadian rhythms are evolutionarily ancient. Bacteria have em. Plants have em. But different molecular tools shape very different clocks, though the same 24 hour cycle is being tracked. 2. The way these rhythms are generated is not through some central system that broadcasts the information to other regions. Instead, it’s instantiated in every cell in the body, and the behavioral rhythm is due to the synchrony between cells. Resonance absolutely plays a role, and has been well documented. The brains role, via the suprachiasmatic nucleus or SCN, is to orchestrate this synchrony, but it is not the source of the rhythms. 3. This slow rhythm definitely regulates cognition (time of day effects in learning, memory formation, recall etc are well documented), but turns out, the molecular mechanisms by which the clock responds to light hugely overlap with the molecular mechanisms of learning in the synapse, and even more recent work has shown clock proteins are actually in the synapses and synaptic activity affects the clock.

All this points to nested oscillators with cross frequency coupling, and even better, because this is all grounded in actual molecular dynamics, there’s plenty of falsifiability. The phase amplitude links are best established for the faster rhythms, the famous “brain waves”. Highly recommend György Buzsáki‘s work on this:

https://www.jneurosci.org/content/32/2/423.short

What’s missing is going down into lower frequency rhythms, and testing how exactly they all couple. We have a lot of the pieces, but no single experimental paradigm that has looked at the full sweep over different times in the same organism. It’s not easy to do, but we’ll get there.

Clock disruption, depending on how you do it, has huge impacts on time perception, cognition, memory, aging AND consciousness. As that data and evidence gets more and more saturated, I hope we see more studies account for chronotype and the internal dynamical state of their test subjects when assessing outcomes.

Obviously I’m biased (also did chronobiology in school), but hopefully I’ve left you curious. Happy to answer more questions all this may have set off.

No one has ever thought that a brain is a desktop computer, and that is not the common usage sense of the term in this context.

Mostly analog, with some threshold-triggered functions and lots of weighted adders and maybe multipliers.

> but how much else will matter remains to be seen!

Indeed, and the similarities between the brains we were born with and the brains we build is tantalizing. I'm really curious about the next chapters of this all.

This is one thing for all of the pairs of genuine friends doing this, but I also have two friends who I introduced to each other exactly once, and who have never spoken since, who have a 6 year snap streak together, and both of whom have streaks like that with dozens of other people, many of whom are virtually strangers.

Mine is showing signs that several of us believe to be dementia, but she refuses to be seen and screened. It has gotten worse over time - repeated conversations, sometimes inside the same phone call, and a shift from "can't remember things if she doesn't write them down" to "needs to ask on multiple occasions because she hasn't remembered to write it down" - but not to the point where she seems to be a danger to herself.

I love my mother, but she is difficult. She also has grown with age. While she is difficult now, she used to be abusive and manipulative. My father would never speak ill of her, but from some things she's said I believe she was worse before she was raising us. If my mother regresses to an earlier state of mind, we will both need professional help. She will need professional care, and I will need help to not internalize the way she treats me.

But you sneak it into your assumptions on what a memory must be.

> However, if you want to identify where long-term memories are stored

And why do you assume there is a specific “where” for the memory?

> then that is in the cortex

There’s good deal of evidence disproving this in the way you’re stating this. The cortex is involved in sensing, and yes, the sensory information associated with a memory will recruit appropriate cortical cells. This doesn’t mean the memory resides in the cortex. And detailed episodic recall keeps recruiting the hippocampus even for old memories, which is odd if the memory were somehow only in the cortex.

> I'm not sure what you are trying to say.

Let me restate what I’m saying then:

There are four claims bundled together in the way you were describing biological memory: that a specific ensemble is activated when a given memory forms; that it’s the same ensemble that gets activated over time when that memory is retrieved; that it’s spatially compact, like a column in region of the brain; and that this ensemble it’s dedicated to that memory, or similar memories .

The first is well supported. An engram, a network of neurons, is indeed activated when a memory first forms, and gets stabilized due to repeated stimulus. Re-activating these neurons in a different context can make the subject (a mouse) behave as it would if it had contextual signals to evoke said memory.

However: 1. This engram is not in one particular part of the brain. There’s a cortical part that overlaps the sensory regions that were involved. But plenty of other regions are part of the engram 2. There’s turnover, over the course of weeks, when the specific cells involved in the engram drift, while the behavior remains stable. 3. The same synapses participate in many memories.

> Memories are presumably stored as embeddings

No. Let’s consider songbirds, which are an excellent worked out example (in an animal without the complex columnar cortical architecture mammals show, by the way).

What’s learned is a temporal sequence, with neurons in a nucleus in their brains each firing one brief burst at a fixed point in the motif, so the content of the memory is its dynamics rather than any value. The circuit that evaluates the match against the tutor template is the same circuit generating the output being evaluated. Song degrades overnight during sleep replay and recovers the next day, and in seasonal species the song nuclei change size across the year with neurons added and lost while the song persists. There’s no read that leaves the item untouched, no persistent address, and no substrate holding still. “Stored as” imports all three.

And it goes below the neuron or synapse. Hearing a tutor song drives immediate early gene expression that habituates with familiarity, and singing drives large transcriptional changes in the song nuclei that differ by social context for the same motor output. Since transcription runs on minutes to hours and the proteins turn over, any persistent state has to be actively regenerated rather than deposited.

TLDR: the memory isn’t a static store. There’s no persistent “location” for it, distributed or otherwise, though specific locations can be in the chain that’s activated for retrieval/production. Instead, memory, over time, is driven by a dynamical regime that adjusts its dynamics to account for the temporal pattern in the salient stimulus.

Nothing, down to the epigenetic changes in the chromatin of these neurons, can be seen as “the” location of “a” memory, especially over time.

> if you are saying that individual memories/chunks are not confined to one set of cells (some localized neural assembly such as a cortical column).

That is indeed the case.

Our model of the world, and this includes "memories" is very highly compressed, and extremely lossy. We reconstruct everything from what neurons activate when we recall something, so it can also be like a corrupted zip, where we don't access everything required in the moment. This can be affected by sleep, stress, hormones, etc.

What is quite interesting is when we try and recall something and can't, but the subconscious processing continues and you recall it later.

I'd say much of it is selected for by evolution. e.g. Most animals don't fight or kill more than they need to since this is not optimal - risk of personal injury and depleting a food resource (there are exceptions of course such as the fox in the henhouse), and this is so universal it seems it has to have a genetic basis.

Religious people would disagree, and the evidences are all to see, hear and ponder from their sacred holy books. But the main questions are that which holy books are truly sacred, meaning that purely and utterly God words. Otherwise it's human innovation/exaggeration or something in between (i.e corrupted God words).

Based on these holy books, religious people adhere and follow their prophets teachings and actions to the best of their ability since the prophets are their fellow human beings and not angels send from the heavens.

Let me make it simple for you.

We have a finite number of neurons in our brain, as do birds, and our brain is attempting to store an ever growing number of memories in those. And, no, this is not a digital computer (is your reading comprehension really so bad?).

Nobody, including you, knows exactly where different types of memory are stored, and for my argument it makes no difference. What does make a difference is how they are represented, which I am suggesting is sparse embeddings.

So far, you've been ignoring my actual argument and instead responding to various strawmen of your own making, so it's not clear if you even understand what a sparse embedding is.

If you do understand, then it should be obvious that it makes no difference whether the neurons comprising this embedding space are in the hippocampus, cortex/pallium or anywhere else. Clearly you do NOT understand, since you bring up bird brains (pallium vs cortex) and want to argue about location of storage (hippocampus vs elsewhere) as if it made a difference to MY argument.

My argument (if you care to respond to it, which so far you have not) is that when sparse embeddings have little to no overlap, then associative recall by a similar pattern will work reliably, but when multiple embeddings have too much in common then recall will suffer as multiple embeddings will match.

Hint: if you think this has anything to do with digital computers then you have misunderstood and need to go back and re-read more carefully, or google for any terms you do not understand.

Eventually after 19 years I wised up.

Resentment started building up and up and up.

Capacity in what sense? Are we saying it’s X MB of data the brain can store? That claim is steeped in assumptions.

On the other hand, no one is claiming the brain has infinite memory or anything. And it’s certainly not a very accurate memory system. I’m arguing against “capacity” being understood as “these specific physical components located here and here we can ID store memories, and can get crowded with too many memories” sense.

This most particularly fails because not all memory is even identical in the brain, whether we mean the physical changes associated, the topology of the information, or how it’s activated.

> There is no reason to believe distributed memory doesn't suffer from the capacity component of the bottleneck.

I didn’t know there was a capacity component to the bottleneck, only a bandwidth one.

All I’m trying to say is that analogy to current typical memory storage systems to explain the brains memory processes is not helpful.

> I guess my point is the brain not being "von Neumann" in architecture or digital is not proof that isn't a "computer" of some sort.

Indeed, since the word computer was first used for humans. But what kind of computer matters enormously. Ising machine? Quantum+classical stack? Reservoir computer? All those frameworks have processes in the brain they can point to as homology.

Which points to a possibility: maybe the brain is multiple types of computers interacting. And the physical realization of these computing architectures aren’t spatially separated but thread through each other in the biochemistry and physical dynamics of cells.

If someone makes an analogy between aspects of A and B, then there is an implicit assumed shared understanding that A & B are DIFFERENT, and what is being pointed out is that they nonetheless may be considered as having something, typically fairly abstract, in common.

Calling a horse's reins as analogous to a cars steering wheel doesn't mean that the person making the analogy can't tell a horse from a car - that would be a very dumb take. A reasonable criticism might be "it's an imperfect analogy since the reins also act as the brake".

If you disagree with an analogy, then you need to address the analogy, not do the dumb take of "a horse is not a car" ("a brain is not a computer").

So, yes, you're "allowed" to "break down" (criticize) the analogy, but please don't just do the dumb take. So, hash key collisions are not analogous to associative recall and sparse embedding overlaps in what way?

I intentionally gave older books and papers. I very clearly understand as does everyone in the field that they are not current or complete. But that awareness is precisely my point.

"Are you saying the brain is a Hopfield network, and that’s it? Because later you indicate otherwise. Kinda confused what I’m to make of it." You being confused by that is kind of my point, it shows the projection you're applying to the entire field. I understand models are wrong and iterative. I also understand the parts that survive, survive in the literature and the field at large. For example, the PNAS paper that showed "hey we think memory is distributed, right? Here's a simple model showing how memory might roughly be stored and recalled via these very simple dynamics over this very simple model. That's cool. Let's build on it." Did I make it clear enough yet that it was simple and wrong? Do you thus believe it wasn't valuable? I guess that would match your confident opinion that the whole field is dummies and of course those dummies cited an incorrect model so much.

If you stopped with saying "we know memory isn't a memory stick and here's the well-established evidence", then I'd fully agree with "Ok, but my argument wasn’t with the OP mentioning capacity, but with their analogy." and would've said nothing. Instead your posture was "I know some specifics based on recent findings that aren't obviously incorporated as of now into the current understanding -- which I refuse to read because it doesn't address precisely this thing only I understand(1) -- , so here is my theory that is certainly novel don't dare try to point me to preexisting literature that might help me refine my theory."

To be clear, I want everyone to explore their ideas and think it's great that you doubt things. But I don't like someone claiming superiority over a field they refuse to understand. And if your doubt something maybe you should check first if there's anyone else doubting it. (Hint: not only did everyone doubt it, they knew it was wrong and they're all actively working on using that doubt to improve it.) Of course a theory that predates a discovery doesn't cover that discover. Of course a simple model of memory isn't a complete model of memory, that was in fact the point! The notion of distributed memory and how it could feasibly work according to dynamics is made more precise than ever before to that time in that paper (among others). And of course it's outdated. But it contains a more precise statement and falsifiable statement of "memory is complicated dynamics and those dummies don't know and also that book is stupid because it doesn't cover X(2,3)" your theory espouses. My issue is with the arrogance and certainty you know best while refusing to actual understand what others think. And thus give no credit to. Science is iterative. Someone has an idea, builds a simple model as proof of concept. Someone else builds on that model precisely where it has holes (whose precise shape only present itself after new experiments motivated in part by the obviously wrong and simplified model and other attempts to break the model). Repeat. Built on the shoulders.. etc.

"Why’s it non-falsifiable? If you do find a single computational paradigm that explains all brain dynamics we can measure, then you have falsified the hypothesis that it’s an integration of multiple computational types.". I said non-falsifiable AND well-accepted. Non-falsifiable was the wrong word. What if I instead said trivially falsified and also adds nothing not known except to the layman who posits an analogy they clearly aren't sure of? Its non-falsifiable relative to the current state of the field, which I now know you're not interested in, because it says nothing not already stated more precisely, as of like 40 years ago.

(1) "As a rule I’ve stopped giving too much time to models that predate the last decades actual mechanistic facts. They’re fun curiosities, but hard to take seriously anymore. Here especially, the absence of astrocytes in the picture makes it hard to buy they have anything real to say about the mechanics at play. " In response to a book that has a lot to say about your new and novel dynamical theory.

(2) A hole it couldn't cover because the experiments and techniques didn't exist at that time. But they knew their theory wasn't complete. They were sharing what was learned up to that point especially the parts that seemed to generalize and survive specifics. That is, an incomplete model they knew was incomplete. But which I promise would help advance your journey.

(3) "Instead, memory, over time, is driven by a dynamical regime that adjusts its dynamics to account for the temporal pattern in the salient stimulus." Which is true and everyone in the field agrees with. And everyone agrees current models don't fully account for everything. Hence their continuing efforts to improve them by accounting for new findings.