Neural Responses to Unexpected Stimulus Repetitions and Omissions in Auditory Cortex Provide Mixed Evidence for Predictive Coding

Humans and other animals process sensory uncertainty by integrating stimulus information with prior knowledge and expectations. Predictive coding conceptualizes perception as a form of Bayesian inference wherein hierarchical brain circuits update internal models to reconcile bottom-up sensory input with top-down predictions. Whereas predictive coding is a leading theory, the extent to which it is implemented in primary sensory cortices remains a matter of debate. To further investigate this issue, we examined single-neuron spiking activity in macaque primary auditory cortex (A1) to expected versus unexpected stimulus repetitions and to expected versus unexpected omissions. On average, we found that A1 neurons did not show enhanced responses to unexpected stimulus repetitions, contrary to predictive-coding theory. However, they did show enhanced responses to unexpected stimulus omissions. Taken together, these mixed results place empirical restraints on how PC is implemented in A1. Significance StatementPerception depends on the brains ability to infer the causes of sensory inputs by integrating new information with prior knowledge under uncertainty. Our results reveal nuanced evidence for predictive coding within the primary auditory cortex (A1). Specifically, spiking activity during unexpected stimuli and unexpected stimulus omissions provide conflicting and supporting, respectively, data for this Bayesian framework. These findings refine our understanding of neural mechanisms underlying perception and provide empirical constraints on the neurobiological implementation of predictive processing.