Decoding fairness motivations from multivariate brain activity patterns
A preference for fairness may originate from prosocial or strategic motivations: we may wish to improve others' well-being or avoid the repercussions of selfish behavior. Here, we used functional magnetic resonance imaging to identify neural patterns that dissociate these two motivations. Participants played both the ultimatum and dictator game (UG-DG) as proposers. Because responders can reject the offer in the UG, but not the DG, offers and neural patterns between the games should differ for strategic players but not prosocial players. Using multivariate pattern analysis, we found that the decoding accuracy of neural patterns associated with UG and DG decisions correlated significantly with differences in offers between games in regions associated with theory of mind (ToM), such as the temporoparietal junction, and cognitive control, such as the dorsolateral prefrontal cortex and inferior frontal cortex. We conclude that individual differences in prosocial behavior may be driven by variations in the degree to which self-control and ToM processes are engaged during decision-making such that the extent to which these processes are engaged is indicative of either selfish or prosocial motivations.
|Keywords||cognitive control, fMRI, machine learning, prosocial behavior, theory of mind|
|Persistent URL||dx.doi.org/10.1093/scan/nsz097, hdl.handle.net/1765/125693|
|Journal||Social cognitive and affective neuroscience|
Speer, S.P.H, & Boksem, M.A.S. (2019). Decoding fairness motivations from multivariate brain activity patterns. Social cognitive and affective neuroscience, 14(11), 1197–1207. doi:10.1093/scan/nsz097