Neurocomputational basis of learning when choices simultaneously affect both oneself and others.

ABSTRACT: Many prosocial and antisocial behaviors simultaneously impact both ourselves and others, requiring us to learn from their joint outcomes to guide future choices. However, the neurocomputational processes supporting such social learning remain unclear. Across three pre-registered studies, participants learned how choices affected both themselves and others. Computational modeling tested whether people simulate how other people value their choices or integrate self- and other-relevant information to guide choices. An integrated value framework, rather than simulation, characterizes multi-outcome social learning. People update the expected value of choices using different types of prediction errors related to the target (e.g., self, other) and valence (e.g., positive, negative). This asymmetr

SUBMITTER: Rhoads SA 

PROVIDER: S-EPMC12546838 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature