Electroencephalographic Correlates of Temporal Bayesian Belief Updating and Surprise

The brain predicts the timing of forthcoming events to optimize responses to them. Such predictions are driven by both prior expectations on the likely timing of stimulus occurrence and the information conveyed by the passage of time (hazard function). Events that violate expectations cause surprise and often induce updating of prior beliefs. Here we combined a Bayesian computational approach with electroencephalography (EEG) to investigate the neural dynamics associated with updating of temporal expectations in the human brain. Moreover, since belief updating is usually highly correlated with surprise, participants performed a temporal foreperiod task that was specifically designed for differentiating between these two processes. The results confirmed that updating and surprise can be functionally distinguished at the EEG level. We isolated two dissociable P3 subcomponents that specifically index the two processes, providing new insights on these event-related potential (ERP) components and their Bayesian interpretation. To the best of our knowledge, the present study delineates ERP correlates of belief updating and surprise about the timing of events for the first time