Download This Paper
Neural Sequences as an Optimal Dynamical Regime for the Readout of Time
25 Pages Posted: 16 Apr 2020 Publication Status: Published
More...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 dynamic regimes, revealed that regimes with higher sequentiality allowed a biologically-constrained artificial downstream network to better read out time. These results suggest that although different strategies exist for encoding time in the brain, neural sequences represent an optimal dynamical regime for enabling downstream areas to read out this information.
Keywords: Timing, Striatum, Premotor cortex, Neural dynamics, Computational model, Neural basis of timing
Suggested Citation: Suggested Citation