Me first: Neural representations of fairness during three-party interactions

NEUROPSYCHOLOGIA

卷:147

Article

Yoder, Keith J.¹  Decety, Jean^1,2 

[1] Univ Chicago, Dept Psychol, 5848 S Univ Ave, Chicago, IL 60637 USA

[2] Univ Chicago Med, Dept Psychiat & Behav Neurosci, Chicago, IL 60637 USA

关键词: Fairness;    Social decision-making;    fMRI;    EEG;    Machine learning;    Egocentric bias;    Neuroeconomics;    Morality;   

DOI  :  10.1016/j.neuropsychologia.2020.107576

来源: Elsevier

【 摘 要 】

One hallmark of human morality is a deep sense of fairness. People are motivated by both self-interest and a concern for the welfare of others. However, it remains unclear whether these motivations rely on similar neural computations, and the extent to which such computations influence social decision-making when self-fairness and other-fairness motivations compete. In this study, two groups of participants engaged in the role of responder in a three-party Ultimatum Game while being scanned with functional MRI (N = 32) or while undergoing high-density electroencephalography (N = 40). In both studies, participants accepted more OtherFair offers when they themselves received fair offers. Though SelfFairness was reliably decoded from scalp voltages by 170 ms, and from hemodynamic responses in right insula and dorsolateral prefrontal cortex, there was no overlap between neural representations of fairness for self and for other. Distinct neural computations and mechanisms seem to be involved when making decisions about fairness in three-party contexts, which are anchored in an egocentric, self-serving bias.

【 授权许可】

Free