Which is why I like @neurograce's point.
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Odgovor korisnicima @MHendr1cks @KordingLab i sljedećem broju korisnika:
But tbh when I have seen the claim "we found nodes in our network with response properties that look like neuron classes" it's usually so general that it's not clear how it couldn't be true, because the classes are OFF / ON / Nothing.
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Odgovor korisnicima @MHendr1cks @KordingLab i sljedećem broju korisnika:
Again, that's not what we're advocating. Lemme give a concrete example: the Sacramento,
@somnirons and Senn model predicts that apical dendrite activity will decrease with error. That's a testable, falsifiable prediction.1 reply 0 proslijeđenih tweetova 2 korisnika označavaju da im se sviđa -
Odgovor korisnicima @tyrell_turing @KordingLab i sljedećem broju korisnika:
I took that article to imply that we shouldn't care whether things like that are true or not. Just molecules?
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Odgovor korisnicima @MHendr1cks @KordingLab i sljedećem broju korisnika:
No! With all due respect, if that's what you thought you completely missed the point. Our point was not: ignore cellular stuff. Our point was: don't try to explain computation cell-by-cell, bc computation emerges from evolutionary and learning optimization processes.
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Odgovor korisnicima @tyrell_turing @MHendr1cks i sljedećem broju korisnika:
The argument is about how to study computation in the brain. It is not claiming that biology doesn't matter, quite the opposite actually.
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Odgovor korisnicima @tyrell_turing @MHendr1cks i sljedećem broju korisnika:
Yea, emphasizing that we should have our eye on learning rules that can actually lead to better performance in a large system doesn't mean having nothing to say about what that looks like on a cellular level. Learning rules are implemented through molecular mechanisms.
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Odgovor korisnicima @neurograce @tyrell_turing i sljedećem broju korisnika:
My wild hot take: 1) this perspective may well be right and if so is super important 4 neuro-theory and AI — I’m investing energy on the idea that it may be right, 2) most important advance in neuro in next 5-10 years will be molecularly annotated connectome. No contradiction.
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Odgovor korisnicima @AdamMarblestone @neurograce i sljedećem broju korisnika:
Totally agree!
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Odgovor korisnicima @tyrell_turing @AdamMarblestone i sljedećem broju korisnika:
What's a molecularly annotated connectome? I'm on the side that a connectome is not going to be that useful but happy to be proved wrong. Certainly the brain has myriad *unseen* mechanisms that contribute to function but not evident in a connectome.
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In C. elegans, it is useful for hypothesis generation and for realizing how ubiquitous signaling relationships that ignore the connectome are. Does very little work constraining circuit models.
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Odgovor korisnicima @MHendr1cks @JasonSynaptic i sljedećem broju korisnika:
The best sketch I have online is this: https://arxiv.org/abs/1404.5103 Think of it as layering a lot of in-situ spatial transcriptomics & proteomics, on top of connectivity, probably all obtained optically & with the benefit of expansion microscopy... would include modulatory receptors.
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Odgovor korisnicima @AdamMarblestone @MHendr1cks i sljedećem broju korisnika:
Ideally: highly multiplexed molecular imaging, including receptors, neuropeptides, ion channel distributions, etc, but with synaptic spatial resolution and in the context of at least sparse connectivity (linking synapses to their parent cells via barcodes) of the same cells.
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