Neural mechanisms of time-forward predictions for naturalistic auditory tone sequences

Prediction of future events is essential for guiding effective actions in dynamic environments. Studies on the neural mechanisms for time-forward predictions have typically used stimuli with relatively simple statistical regularities. Here, we investigated time-forward predictions using stimuli containing statistical regularities similar to those found in natural auditory stimuli. Using intracranial EEG recordings in neurosurgical patients, we found that prediction signals were primarily carried by low-frequency activity across widespread cortical regions, including sensory, parietal, and frontal areas. Prediction-error (PE) signals were found in both low- and high-frequency activity, with high-frequency components localized mainly to sensory areas. Contrary to previous hypotheses, prediction and PE signals did not show a clear spatial or spectral segregation. Directed connectivity between brain regions decreased over the course of the stimulus sequence as predictability increased, except for pathways originating from the parietal cortex. These results reveal integrative and distributed predictive processing and highlight the dorsal auditory pathway in time-forward prediction. A longstanding question is how the brain predicts complex, naturalistic sensory events and updates those predictions when expectations are violated. Using intracranial recordings, the authors show that prediction and prediction-error signals are distributed across cortical networks in ways that challenge classical predictive coding models, while highlighting a central role for the dorsal auditory pathway in time-forward prediction.