Disentangling the roles of dimensionality and cell categories in neural computations
Friday, June 19, 2020
13:00 UTC
Dr. Srdjan Ostojic
École Normale Supérieure
Recording
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Hosted by The Neurotheory Forum70 minutes
Abstract
The description of neural computations currently relies on two competing views: (i) a classical single-cell view that aims to relate the activity of individual neurons to sensory or behavioural variables, and organize them into functional classes; (ii) a more recent population view that instead characterises computations in terms of collective neural trajectories, and focuses on the dimensionality of these trajectories as animals perform tasks. How the two key concepts of functional cell classes and low-dimensional trajectories interact to shape neural computations is however at present not understood. Here I will address this question by combining machine-learning tools for training recurrent neural networks with reverse-engineering and theoretical analyses of network dynamics.
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