Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG

Abstract

Hoy et al. combine behavioral modeling and single-trial EEG regression to disentangle sequential prediction errors in an interval timing task, which dissociated outcome valence, magnitude, and probability in human participants. Their study reconciles debates on the sequence of components representing reward and salience prediction errors in the human EEG.