Prefrontal neural ensembles encode an internal model of visual sequences and their violations

Theories of predictive coding hypothesize that cortical networks learn internal models of environmental regularities to generate expectations that are constantly compared with sensory inputs. The prefrontal cortex (PFC) is thought to be critical for predictive coding. Here, we show how prefrontal neuronal ensembles encode a detailed internal model of sequences of visual events and their violations. We recorded PFC ensembles in a visual "local-global" sequence paradigm probing low and higher-order predictions and mismatches. PFC ensembles formed distributed, overlapping representations for all aspects of the dynamically unfolding sequences, including information about image identity as well as abstract information about ordinal position, anticipated sequence pattern, mismatches to local and global structure, and model updates. Model and mismatch signals were mixed in the same ensembles, suggesting a revision of predictive processing models that consider segregated processing. We conclude that overlapping prefrontal ensembles may collectively encode all aspects of an ongoing visual experience, including anticipation, perception, and surprise.