| Paper: | PS-1B.44 | ||
| Session: | Poster Session 1B | ||
| Location: | H Fläche 1.OG | ||
| Session Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation: | Poster | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | A Neuro-Computational Characterization of Theory of Mind Processes during Cooperative Interaction | ||
| Manuscript: | Click here to view manuscript | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
||
| DOI: | https://doi.org/10.32470/CCN.2019.1051-0 | ||
| Authors: | Tessa Rusch, University Hamburg, Germany; Prashant Doshi, University of Georgia, United States; Martin Hebart, National Institute of Mental Health, United States; Saurabh Kumar, University Hamburg, Germany; Michael Spezio, Scripps College, United States; Jan Gläscher, University Hamburg, Germany | ||
| Abstract: | Humans are distinctly skilled at cooperation. To successfully engage with others they apply Theory of Mind (ToM). Here, we investigate neuro-computational mechanisms underlying ToM during real-time dyadic coordination in a probabilistic social decision game. To effectively coordinate participants have to represent the surrounding they interacted in and simultaneously simulate their partner’s representation of the world. These cognitive computations are formalized with a decision framework that combines decision-making under uncertainty with intentional models of other agents. Using model-based EEG analyses, we identify oscillatory signals related to errors experienced by players when own expectations towards the surroundings are violated and simulations of errors experienced by the partner when the partner’s predictions fail. Consistent with previous studies, we find positive correlations between power in frontal delta and theta oscillations and experienced errors. Most strikingly, these signals are also found in relation to simulations of the partner’s error, at times when participants themselves experience no prediction error themselves. These findings unveil the neural signature of a crucial computational component of the mental model of a partner and demonstrate that the brain recruits similar mechanisms for simulation the decisions of others as for computing one’s own decision. | ||