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AdamMarblestone's profile
Adam Marblestone
Adam Marblestone
Adam Marblestone
@AdamMarblestone

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Adam Marblestone

@AdamMarblestone

Technologist, Scientist

adammarblestone.org
Joined February 2009

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    1. David A. Markowitz‏ @neurowitz 28 Nov 2019
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      The key word here is mechanisms. How do we move beyond identifying neural correlates of behaviorally-relevant variables and address mechanisms? Can we back it out of long recordings involving multiple tasks / unconstrained behavior, without the need for optogenetic manipulations?

      3 replies 1 retweet 4 likes
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    2. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @neurowitz

      A possibility, much discussed of late: u don’t need / there aren’t understandable mechs for every computation. U need to know just the fundamental mechs that *generate* those diverse comp’s, e.g., cost fxn opt. w/ good credit assignment. Doubt can crack those w/ just recording!

      1 reply 0 retweets 2 likes
    3. David A. Markowitz‏ @neurowitz 28 Nov 2019
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      Replying to @AdamMarblestone

      I don't disagree this is a useful line of inquiry. But with all we're learning about cell types and cell/compartment-specific interactions in the brain, it seems likely there is a mechanistic basis of neural computation yet to be discovered.

      2 replies 0 retweets 0 likes
    4. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @neurowitz

      Yep and I personally doubt we’ll see either the opt mechanism (if any) or the more specific computational built-ins you’re referring to, with pure recording minus perturbation and connectomics.

      1 reply 0 retweets 0 likes
    5. David A. Markowitz‏ @neurowitz 28 Nov 2019
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      Replying to @AdamMarblestone

      If that's true, and cell type-specific perturbation during behavior is required, this will be a very long slog in rodents and near impossible in primates. (I'm more optimistic about connectomics become easy across the board.)

      1 reply 0 retweets 1 like
    6. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @neurowitz

      Now I start to see why you asked the question!

      1 reply 0 retweets 0 likes
    7. David A. Markowitz‏ @neurowitz 28 Nov 2019
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      Replying to @AdamMarblestone

      It seems likely we can use ML to discover candidate mechanistic models that explain neural data even without constraints from optogenetics or connectomics. Something like a GNN trained to reproduce an animal's task performance and regularized with neural data.

      1 reply 0 retweets 3 likes
    8. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @neurowitz

      I guess I’m very sympathetic to that as an approach to improve AI (see recent Tolias paper) but not necessarily as heavily constraining “mechanism”... though one *could* get lucky if one can converge into the right equivalence class of mechanism by fitting enough data...

      1 reply 0 retweets 0 likes
    9. David A. Markowitz‏ @neurowitz 28 Nov 2019
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      Replying to @AdamMarblestone

      How much data would be enough? (As if anyone knows!) My motivating question assumed access to activity by every neuron in a region of the brain under many different behavioral conditions. Data from multiple regions could only help, obvs.

      1 reply 0 retweets 1 like
    10. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @neurowitz

      A probably under-appreciated aspect of our present predicament. Yes, DL is just fitting. But, if you fit *enough* real neurons, behavior, functional performance, arch constraints... you’ll at least get some interesting partial clone of the comp’s that evolution & culture built.

      2 replies 0 retweets 1 like
      Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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      Replying to @AdamMarblestone @neurowitz

      True of C. Elegans and true for You.

      9:37 AM - 28 Nov 2019
      1 reply 0 retweets 0 likes
        1. Adam Marblestone‏ @AdamMarblestone 28 Nov 2019
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          Replying to @AdamMarblestone @neurowitz

          Computational universality FTW

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