Latent learning drives sleep-dependent plasticity in distinct CA1 subpopulations

Abstract

Latent learning allows the brain the transform experiences into cognitive maps, a form of implicit memory, without reinforced training. Its mechanism is unclear. We tracked the internal states of the hippocampal neural ensembles and discovered that during latent learning of a spatial map, the state space evolved into a low-dimensional manifold that topologically resembled the physical environment. This process requires repeated experiences and sleep in-between. Further investigations revealed that a subset of hippocampal neurons, instead of rapidly forming place fields in a novel environment, remained weakly tuned but gradually developed correlated activity with other neurons. These weakly spatial neurons bond activity of neurons with stronger spatial tuning, linking discrete place fields into a map that supports flexible navigation.