Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits.

ABSTRACT: Adaptive sequential behavior is a hallmark of human cognition. In particular, humans can learn to produce precise spatiotemporal sequences given a certain context. For instance, musicians can not only reproduce learned action sequences in a context-dependent manner, they can also quickly and flexibly reapply them in any desired tempo or rhythm without overwriting previous learning. Existing neural network models fail to account for these properties. We argue that this limitation emerges from the fact that sequence information (i.e., the position of the action) and timing (i.e., the moment of response execution) are typically stored in the same neural network weights. Here, we augment a biologically plausible recurrent neural network of cortical dynamics to include a basal ganglia-thalamic

SUBMITTER: Calderon CB 

PROVIDER: S-EPMC8843237 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature