Electroencephalographic correlates of temporal Bayesian belief updating and surprise

NeuroImage

Ettore Ambrosini¹  Mariagrazia Capizzi²  Antonino Vallesi³  Antonino Visalli⁴  Bruno Kopp⁴ 

[1] Corresponding authors at: Department of Neuroscience, University of Padova, 35128 Padova, Italy;Department of General Psychology, University of Padova, 35131 Padova, Italy;Department of General Psychology, University of Padova, 35131 Padova, Italy;Department of Neuroscience, University of Padova, 35128 Padova, Italy;

关键词: Bayesian brain;    Foreperiod paradigm;    Hazard function;    Surprise;    Belief updating;    P3;   

DOI  :  

来源: DOAJ

【 摘 要 】

The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that neural encoding of surprise comprises neural activity in the cingulo-opercular network (CON) and parietal regions. These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/

【 授权许可】

Unknown