Neural Sequences as an Optimal Dynamical Regime for the Readout of Time.

ABSTRACT: Converging evidence suggests that the brain encodes time through dynamically changing patterns of neural activity, including neural sequences, ramping activity, and complex spatiotemporal dynamics. However, the potential computational significance and advantage of these different regimes have remained unaddressed. We combined large-scale recordings and modeling to compare population dynamics between premotor cortex and striatum in mice performing a two-interval timing task. Conventional decoders revealed that the dynamics within each area encoded time equally well; however, the dynamics in striatum exhibited a higher degree of sequentiality. Analysis of premotor and striatal dynamics, together with a large set of simulated prototypical dynamical regimes, revealed that regimes with higher s

SUBMITTER: Zhou S 

PROVIDER: S-EPMC7825362 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature