Learning to predict future locations with internally generated theta sequences.

ABSTRACT: Representing past, present and future locations is key for spatial navigation. Indeed, within each cycle of the theta oscillation, the population of hippocampal place cells appears to represent trajectories starting behind the current position of the animal and sweeping ahead of it. In particular, we reported recently that the position represented by CA1 place cells at a given theta phase corresponds to the location where animals were or will be located at a fixed time interval into the past or future assuming the animal ran at its typical, not the current, speed through that part of the environment. This coding scheme leads to longer theta trajectories, larger place fields and shallower phase precession in areas where animals typically run faster. Here we present a mechanistic computation

SUBMITTER: Parra-Barrero E 

PROVIDER: S-EPMC10208522 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature