To make adaptive decisions in a social context, humans must identify relevant agents in the environment, infer their underlying strategies and motivations, and predict their upcoming actions. We used functional magnetic resonance imaging (fMRI), in conjunction with combinatorial multivariate pattern analysis (MVPA), to predict human participants’ subsequent decisions in an incentive-compatible poker game. We found that signals from the temporal-parietal junction (TPJ) provided unique information about the nature of the upcoming decision, and that information was specific to decisions against agents who were both social and relevant for future behavior.
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