Encoding time in neural dynamic regimes with distinct computational tradeoffs.

ABSTRACT: Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required pr

SUBMITTER: Zhou S 

PROVIDER: S-EPMC8893702 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature