[HN Gopher] Learning produces a hippocampal cognitive map in the...
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Learning produces a hippocampal cognitive map in the form of a
state machine
Author : sebg
Score : 173 points
Date : 2023-08-11 01:57 UTC (2 days ago)
(HTM) web link (www.biorxiv.org)
(TXT) w3m dump (www.biorxiv.org)
| Animats wrote:
| Actual paper text.[1]
|
| How the mouse's brain is scanned, very intrusively.[2] That's
| both impressive and scary. They're scanning the surface of part
| of the brain at a good scan rate at high detail. They're seeing
| the activation of individual neurons. This is much finer detail
| than non-intrusive functional MRI scans.
|
| Does the data justify the conclusions? The maze being used is a
| simple T-shaped maze. The "state machine" supposedly learned is
| extremely simple. They conclude quite a bit about the learning
| mechanism from that. But now that they have this experimental
| setup working, there should be more results coming along.
|
| [1]
| https://www.biorxiv.org/content/10.1101/2023.08.03.551900v2....
|
| [2]
| https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-01...
| ImHereToVote wrote:
| So technically we have the technology to simulate a human
| brain. Just not anywhere near real time. And not at any
| semblance of reasonable cost. And not guaranteed to simulate
| the important parts.
| marcosdumay wrote:
| If you mean it on the trivial meaning that "computers most in
| principle be able to simulate a brain", then yes, and it has
| been obvious for many decades already.
|
| If you want to say that we know what algorithms to use to
| simulate a brain, then no, and this paper is one advance on
| the goal of knowing those algorithms. But it does not go all
| the way there.
| aatd86 wrote:
| At the civilian level. Who knows what exists out there... :|
| jiggawatts wrote:
| The civilian level is the state of the art. The chip
| industry is at the cutting edge, there is nothing beyond it
| that is available _at scale_ , and in this instance: scale
| matters!
|
| There are some small exceptions of course: RSFQ digital
| logic is insanely fast (hundreds of gigahertz), but nobody
| has scaled it to large integrated circuits.
|
| Supercomputers are built with somewhat esoteric parts, but
| not secret unobtainium. At least in principle the same RDMA
| switches and network components are commercially available.
| Similarly, the specialised CPUs like the NVIDIA Grace
| Hopper are available, although I doubt any wholesalers have
| it in stock!
|
| To believe otherwise is to believe that governments
| (plural!) have secretly hidden tens of billions in cutting
| edge chip fabs, tens of billions of chip design shops, and
| more.
|
| In reality the government buys their digital electronics
| from the same commercial suppliers you and I do.
|
| Only a handful of specialised circuits are made in secret,
| such as radar amplifiers.
| aatd86 wrote:
| Are processors and processor speed the only limiting
| factor in terms of applications? (probably that they are
| fast enough anyway, could be a non-factor, communication
| between neuron is not that fast compared to clock speed
| if I remember well)
|
| Especially in an era in which the recorded data can be
| fed to an algorithm that can approximate dynamic brain
| maps with more or less accuracy?
| jiggawatts wrote:
| One concern is the lack of ethics, or more accurately,
| the different ethical considerations in the spy agencies.
|
| They have every motivation to capture personal phone
| calls and text chats in bulk and run them all through an
| LLM-like training regime so that they can ask it
| questions like: "Does so-and-so plan a terrorist attack?"
|
| Somewhere out there in an NSA data centre there is a
| model being trained on your emails, right now.
| 60654 wrote:
| There appear to be two _very_ interesting results:
|
| 1. We can observe how the state machine gets generated, first
| just a jumble of locations in a hub and spokes topology (no
| correlations), then some correlations start happening pairwise,
| making a kind of a beads on a string topology, and then finally
| the mental model snaps marvelously to two completely separate
| paths that meet at ends. It's amazing to see these mental
| models get formed _in vivo_ out of initial unstructured
| perceptions.
|
| 2. In addition to standard HMM modeling, authors find that a
| "biologically plausible recurrent neural network (RNN) trained
| using Hebbian learning" can mimic some of this (but not
| exactly). But more interestingly, they find that LSTMs or
| transformers _cannot_. Which makes sense structurally, but it
| 's a good reminder for those who believe the anthropomorphic
| hype that transformers have memory or other such (they don't :)
| ).
|
| The scanning is indeed very intrusive, though.
| calf wrote:
| Couldn't memoryless neural networks still possibly learn the
| Next-State function of a Finite-State machine? Depending on
| the training algorithm. Especially if the eventual usage of
| such networks is to be called over and over again to generate
| the next token; conceptually this to me seems analogous to
| the process of finitely unrolling a while loop or a computer
| pipeline.
| padolsey wrote:
| It seems to reflect the general way we understand the brain
| right? Wiring together/firing together? Then ~ abra cadabra ~
| meaningful blobs of brain buzzy stuff emerge from seemingly
| simple rules? It seems beautifully pure that mind maps are
| literally "mind maps" in a sense, a bit like we have grid cells
| arranged proximally to mirror physical spaces as we walk through
| them.
| samstave wrote:
| We need to study hummingbirds deeper, and ravens
|
| They have the largest hippocampus to brain ratio and have 3D
| spatial memory of all their food source locations as well as
| (with ravens) who their human enemies are.
|
| We can learn a lot about memory from these birds
| pizzafeelsright wrote:
| Teaching my kid has been fun and educational.
|
| The rule in the house is we don't say "I don't know." If we don't
| know something, we are required to think about it and then ask a
| question.
|
| Recently, he asked how an audio recoding dog trainer worked in
| terms of how it "went back up" because he couldn't see the
| internals. He knew that it went down and back up, and then knew
| that it was not electronic, but mechanical. I asked him to think
| about it. He thought, and I could see his mind working, thinking
| about everything in his mind where a toy of his would go down and
| up. He sat for around 20 seconds and asked, is it a spring? I was
| quite impressed considering he is 4 years old and was able to
| come to this conclusion.
|
| There is a map we create, a list of things that go up and down.
| From that list of things that can go up and down, knowing it was
| not a pulley or a plunger, because it returned to its original
| state, he's able to limit it to the one object that would work.
|
| The biggest jumps in my education have been directly related to
| people mapping Concepts and ideas instead of memorization. That's
| like the idea that everything is a file. From that framework you
| can pull out questions like, can I read, do I have permissions to
| read, can I write, so now when someone explains to me I knew
| shiny object, like a fancy Wiz Bang database, I asked a couple
| questions and generally know how it works.
| aio2 wrote:
| That's something I do too, but a bit modified: instead of going
| to someone about a problem, we try and figure it out instead,
| and if we can't, we go and ask help while explaining our
| original solution.
| throwaway290 wrote:
| (in mice)
| SubiculumCode wrote:
| There are some important differences between mice and human
| hippocampi, including different long range
| connections...however the overall patterns of organization
| across the hippocampal subfields e.g. heavy recurancy in CA3,
| sparse separation of signals in dentate gyrus, etc...these are
| very similar in structure and response patterns between
| species. ..gotta love the spiking data in human epilepsy
| patients
| insanitybit wrote:
| My naive perspective is that the foundational properties of the
| brain are probably really similar between mice and humans. For
| example, we have put human brain cells into rats and the brain
| cells have done... something.
|
| The chemistry is probably different in a bunch of ways "rats
| evolved to use this hormone to feel X, we use it to tell us Y"
| or some other such thing, but structurally I'd imagine that
| neurons function similarly.
|
| Anyone know more?
| chaxor wrote:
| Lack of Wernicke's and semantic representation similarity is
| a big difference for one
| convolvatron wrote:
| even if there are structural differences, just the fact that
| we can establish a loose isomorphism between our knowledge
| about computational models and the cognitive processes of any
| living creature seems like a really profound step forward for
| cognitive science if it holds up.
|
| there isn't any issue about clinical relevance
| insanitybit wrote:
| I agree
| xjay wrote:
| 2020-12: Some research done with human subjects regarding how
| the brain reacts when we're reading code.
|
| > The researchers saw little to no response to code in the
| language regions of the brain. Instead, they found that the
| coding task mainly activated the so-called multiple demand
| network. This network, whose activity is spread throughout the
| frontal and parietal lobes of the brain, is typically recruited
| for tasks that require holding many pieces of information in
| mind at once, and is responsible for our ability to perform a
| wide variety of mental tasks. [1]
|
| [1] https://news.mit.edu/2020/brain-reading-computer-code-1215
| Nowado wrote:
| It bothers me way less when it's not a medical treatment
| research.
| giardini wrote:
| tl;dr or ELI5 please?
| gridspy wrote:
| A hidden state machine plus a neural net appears to be similar
| to how mice learn to navigate a maze.
|
| If you hold them still and probe their brain while they
| navigate in VR you see a state-machine map appear in their
| mind. That map varies if the VR map varies.
| x86x87 wrote:
| The brain is just a bunch of ifs
| hanniabu wrote:
| I really hate how people always try to put programming labels on
| brain activity
|
| "This is a state machine", "this is a natural net", "it's running
| a coroutine", "it's garbage collection"...
| mdp2021 wrote:
| Good news (are suggested) since the hippocampus is one of the few
| places in which neural regeneration is possible.
| bannedbybros wrote:
| [dead]
| ilaksh wrote:
| They mention an RNN with Hebbian learning. What's the SOTA for
| that? I found this: https://github.com/JonathanAMichaels/hebbRNN
|
| Is there anything optimized for GPU or TPU?
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