Parametric control of flexible timing through low-dimensional neural manifolds
Manuel Beiran · Center for Theoretical Neuroscience, Columbia University & Rajan lab, Icahn School of Medicine at Mount Sinai
Wed, Mar 9, 2022 · 17:00 UTC
Biological brains possess an exceptional ability to infer relevant behavioral responses to a wide range of stimuli from only a few examples. This capacity to generalize beyond the training set has been proven particularly challenging to realize in artificial systems. How neural processes enable this capacity to extrapolate to novel stimuli is a fundamental open question. A prominent but underexplored hypothesis suggests that generalization is facilitated by a low-dimensional organization of collective neural activity, yet evidence for the underlying neural mechanisms remains wanting. Combining