Flexible multitask computation in recurrent networks utilizes shared dynamical motifs
Laura Driscoll · Stanford University
Fri, Aug 26, 2022 · 17:00 UTC
Flexible computation is a hallmark of intelligent behavior. Yet, little is known about how neural networks contextually reconfigure for different computations. Humans are able to perform a new task without extensive training, presumably through the composition of elementary processes that were previously learned. Cognitive scientists have long hypothesized the possibility of a compositional neural code, where complex neural computations are made up of constituent components; however, the neural substrate underlying this structure remains elusive in biological and artificial neural networks. He