Feedback From Facial Expressions Contribute to Slow Learning Rate in an Iowa Gambling Task

Abstract

Facial expressions of emotion can convey information about the world and disambiguate elements of the environment, thus providing direction to other people’s behavior. However, the functions of facial expressions from the perspective of learning patterns over time remain elusive. This study investigated how the feedback of facial expressions influences learning tasks in a context of ambiguity using the Iowa Gambling Task. The results revealed that the learning rate for facial expression feedback was slower in the middle of the learning period than it was for symbolic feedback. No difference was observed in deck selection or computational model parameters between the conditions, and no correlation was observed between task indicators and the results of depressive questionnaires.

Publication
Frontiers in Psychology.
Shushi Namba
Shushi Namba
Researcher

My research interests include distributed facial expression,computational modeling and programmable matter.