ATTRACTOR-BASED MODELS FOR SEQUENCES AND PATTERN GENERATION IN NEURAL CIRCUITS.

ABSTRACT: Neural circuits in the brain perform a variety of essential functions, including input classification, pattern completion, and the generation of rhythms and oscillations that support processes such as breathing and locomotion [51]. There is also substantial evidence that the brain encodes memories and processes information via sequences of neural activity. In this dissertation, we are focused on the general problem of how neural circuits encode rhythmic activity, as in central pattern generators (CPGs), as well as the encoding of sequences. Traditionally, rhythmic activity and CPGs have been modeled using coupled oscillators. Here we take a different approach, and present models for several different neural functions using threshold-linear networks. Our approach aims to unify attrac

SUBMITTER: Curto C 

PROVIDER: S-EPMC11527095 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature