TY - JOUR
T1 - Electroencephalographic correlates of temporal Bayesian belief updating and surprise
AU - Visalli, Antonino
AU - Capizzi, Mariagrazia
AU - Ambrosini, Ettore
AU - Kopp, Bruno
AU - Vallesi, Antonino
N1 - Funding Information:
This work was partly funded by the European Research Council (ERC starting grant LEX-MEA, no. 313692 , to A.Va). The first author acknowledges the support of the Boehringer Ingelheim Fonds in the form of a Travel Grant for his research period in the Lab of Prof. Kopp.
Publisher Copyright:
© 2021
PY - 2021/5/1
Y1 - 2021/5/1
N2 - 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/
AB - 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/
KW - Bayesian brain
KW - Belief updating
KW - Foreperiod paradigm
KW - Hazard function
KW - P3
KW - Surprise
UR - http://www.scopus.com/inward/record.url?scp=85101371395&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101371395&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2021.117867
DO - 10.1016/j.neuroimage.2021.117867
M3 - Article
C2 - 33592246
AN - SCOPUS:85101371395
VL - 231
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
M1 - 117867
ER -