摘要:To learn through feedback, feedback should be reliable. However, if feedback is blurred by irrelevant social information, learning in a volatile environment, which requires fast learning and adaptation, might be disturbed. In this study, we investigated how feedback with social noise interferes with learning in a volatile environment by designing a probabilistic associative learning task in which the association probability changes dynamically, and the outcome was randomly blurred by an emotional face with incongruent valence. Learning in this situation was modelled by HGF-S such that emotionally incongruent feedback induces perceptual uncertainty called social noise. The Bayesian model comparison showed that the HGF-S model explains the subjects' behaviour well, and the simulation showed that social noise interrupts both learning the association probability and the volatility. Furthermore, the learning interruption influenced the subsequent decision. Finally, we found that the individual difference in how the same emotionally incongruent feedback induces social noise in varying degrees was related to the differences in event-related desynchronization induced by happy and sad faces in the right anterior insula, which encodes the degree of emotional feeling. These results advance our understanding of how feedback with emotional interference affects learning.