Aspirational. This is how I want to spend my available time.
652 karma · joined April 15, 2019
It's more about computational complexity it seems but maybe it cites stuff that might interest you.
It's using computational neural networks that no one has ever believed represent the biology of the brain, but I think I must still disclose the following to save the precious time of the genius solving the problem all by himself:
It doesn't fully account for every biological detail ever documented, so it's probably a meaningless "curiosity".
Oh it probably also doesn't account for every detail discovered since publication so even if had value at time of publication it is not worth reading now.
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.
"All I’m trying to say is that analogy to current typical memory storage systems to explain the brains memory processes is not helpful." Again, my impression is that the original author's idea was about capacity in general, then he gave an analogy. The analogy was wrong, but your reply went way beyond his specific analogy to the extreme of discarding memory itself as useful concept. To be clear, I agree that it is distributed and lossy and time-dependent. I agree it is not just a simple read-off of a static chunk with a fixed address.
"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."
I would say that is both non-falsifiable and well-accepted.
https://mitpress.mit.edu/9780262041997/theoretical-neuroscie... might interest you and on the other end bialek's spikes shows quite a bit actual does happen near the single neuron limit. bialek also does/did a lot of other stuff on capacities and processing you might be interested in. https://mitpress.mit.edu/9780262181747/spikes/
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.
*btw, if the money went toward interest on debt, all else being equal, that is money back in to the future economy via reduced tax demand. Of course this won't actually happen and the government will spend every cent it gets and more. So maybe your opposition should be with the government and not LVT?
Would decoupling education funding from local taxes do anything? I'm thinking maybe it decreases the incentive to hold on to a house thus increasing effective mobility/geographic diffusion? Probably a small effect but it seems possible it could have second order effects.
But also, he made predictions of the near future in his time. They were incorrect. No updates were made. Those who did try to refine and update his ideas are far less influential. His original theory survives like gospel. I wish I could say only by non-academics.
Edit - back to economics. It's funny. I would say in economics the closest thing we have to double blind wrt economic systems is socialism/communism vs. capitalism. It's clearly not a true double blind. But also clearly some people just don't care to feed that data back in to their models. Because they aren't scientific.
Edit- I don't know what's controversial about this? Feedback is the self-correcting piece.
fMRI is one of the best tools we have, but that doesn't mean it's good. fMRI shit should always be taken with spoon of salt. source: a bunch of grad school friends in neuroscience and psychology a few years ago.
"on two patients whose language networks were destroyed by stroke, plus fMRI on healthy volunteers solving the same puzzles silently. Both lines of evidence point the same way: the language network sits out during reasoning." that doesn't mean they didn't learn the meta-ability of how to solve such things without language. You can learn something with language, move it to a separate "database" in some abstracted form then pull from that "database" from a non-language component. In fact I would think the language-isn't-thinking people would favor an explanation where the thinking ability is stored independently of language. I guess my point is that no "language" component being lit up during a specific reasoning task doesn't exclude the possibility we learned that specific reasoning algorithm (for lack of a better word) via language + other things.
TL;DR maybe this specific "logic" ability is a learned-via-language+ component of the brain. Language not being active during that puzzle could just mean language+ generated that component and stored it in a more abstract form than language.
I guess I'm on the opposite end. I think many people will have any idea what a ground state is and those very people will come away most confidently believing physicists don't understand shit.
I never personally got the least bit excited about Sora or nanobanana or whatever video/audio generation thing. But I guess I'm just not their customer. I do love the read-side of it though.