| Literature DB >> 32758554 |
Abstract
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.Entities:
Keywords: EEG; Egocentric bias; Fairness; Machine learning; Morality; Neuroeconomics; Social decision-making; fMRI
Mesh:
Year: 2020 PMID: 32758554 PMCID: PMC7554091 DOI: 10.1016/j.neuropsychologia.2020.107576
Source DB: PubMed Journal: Neuropsychologia ISSN: 0028-3932 Impact factor: 3.139