Neuroscience thought problem: Someone gives you simultaneously recorded spike trains (ms resolution) from every neuron in a region of the brain under multiple task conditions. No connectome. What analysis tools do you deploy to study mechanisms by which circuits support behavior?
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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.
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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...
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