Hybrid predictive coding: Inferring, fast and slow.

ABSTRACT: Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors"-the differences between predicted and observed data. Implicit in this proposal is the idea that successful perception requires multiple cycles of neural activity. This is at odds with evidence that several aspects of visual perception-including complex forms of object recognition-arise from an initial "feedforward sweep" that occurs on fast timescales which preclude substantial recurrent activity. Here, we propose that the feedforward sweep can be understood as performing amortized inference (applying a learned function that maps directly from data to beliefs) and recurrent processing can be understood as performing iterativ

SUBMITTER: Tscshantz A 

PROVIDER: S-EPMC10395865 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature