Inferring context-dependent computations through linear approximations of prefrontal cortex dynamics.

ABSTRACT: The complex neural activity of prefrontal cortex (PFC) is a hallmark of cognitive processes. How these rich dynamics emerge and support neural computations is largely unknown. Here, we infer mechanisms underlying the context-dependent integration of sensory inputs by fitting dynamical models to PFC population responses of behaving monkeys. A class of models implementing linear dynamics driven by external inputs accurately captured PFC responses within contexts and revealed equally performing mechanisms. One model implemented context-dependent recurrent dynamics and relied on transient input amplification; the other relied on subtle contextual modulations of the inputs, providing constraints on the attentional effects in sensory areas required to explain flexible PFC responses and behavior.

SUBMITTER: Soldado-Magraner J 

PROVIDER: S-EPMC11654703 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature