Cortical networks with multiple interneuron types generate oscillatory patterns during predictive coding.

ABSTRACT: Predictive coding (PC) proposes that our brains work as an inference machine, generating an internal model of the world and minimizing predictions errors (i.e., differences between external sensory evidence and internal prediction signals). Theoretical models of PC often rely on high-level approaches, and therefore implementations detailing which neurons or pathways are used to compute prediction errors or adapt the internal representations, as well as their level of agreement with biological circuitry, are currently missing. Here we propose a computational model of PC, which integrates a neuroanatomically informed hierarchy of two cortical areas with a simplified laminar organization and cell-type-specific connectivity between excitatory, PV, SST and VIP cells. Our model efficiently perfo

SUBMITTER: Lee K 

PROVIDER: S-EPMC12443261 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature