PSYC Seminar: “CHASE – A Bayesian model for characterizing mentalization during strategic interactions”, Gökhan Aydoğan, 12:30Noon May 2 2024 (EN)

Please join Bilkent University’s Psychology Department on Thursday for the visit of Dr Gökhan Aydoğan.

Speaker: Gökhan Aydoğan, University of Zurich

“CHASE – A Bayesian model for characterizing mentalization during strategic interactions”

Date: Thursday, 2 May 2024
Time: 12:30
Room: C Amphitheatre

Mentalization–inferring other’s emotions and intentions–is crucial for human social interactions and is impaired in various brain disorders. While previous neuroscience research has focused on static mentalization strategies, we know little about how the brain decides adaptively which strategies to employ at any moment of time. Here we investigate this core aspect of mentalization with computational modeling and fMRI during interactive strategic games. We find that most participants can adapt their strategy to the changing sophistication of their opponents, but with considerable individual differences. Model-based fMRI analyses identify a distributed brain network where activity tracks this mentalization-belief adaptation. Notably, the extent to which people update their belief about the other’s sophistication can be predicted out-of-sample from neural activity, providing a neural fingerprint of adaptive mentalization. Our approach illuminates the neural basis of mentalization ability and provides a new approach to assess these capabilities in healthy and clinical populations.

About the speaker:
Gökhan Aydoğan is a post-doctoral scholar at the Zurich Center for Neuroeconomics, University of Zurich. He completed his Ph.D. in Economics at Ludwig-Maximilians-University Munich, with further academic training in Neuroeconomics at the University of California, Berkeley and at the Arizona State University. Dr Aydoğan’s research interests encompass Neuroeconomics, Neurogenomics, and Social Neuroscience, with a specialized focus on Neurocomputational Modeling of Social Behavior. In his work, he primarily adopts a neurocomputational approach to probe the underpinnings of economic behavior, leveraging findings that show the brain represents sensory information probabilistically rather than in absolute terms.