Literature DB >> 24396005

Neural basis of increased costly norm enforcement under adversity.

Yan Wu1, Hongbo Yu2, Bo Shen2, Rongjun Yu2, Zhiheng Zhou2, Guoping Zhang1, Yushi Jiang2, Xiaolin Zhou3.   

Abstract

Humans are willing to punish norm violations even at a substantial personal cost. Using fMRI and a variant of the ultimatum game and functional magnetic resonance imaging, we investigated how the brain differentially responds to fairness in loss and gain domains. Participants (responders) received offers from anonymous partners indicating a division of an amount of monetary gain or loss. If they accept, both get their shares according to the division; if they reject, both get nothing or lose the entire stake. We used a computational model to derive perceived fairness of offers and participant-specific inequity aversion. Behaviorally, participants were more likely to reject unfair offers in the loss (vs gain) domain. Neurally, the positive correlation between fairness and activation in ventral striatum was reduced, whereas the negative correlations between fairness and activations in dorsolateral prefrontal cortex were enhanced in the loss domain. Moreover, rejection-related dorsal striatum activation was higher in the loss domain. Furthermore, the gain-loss domain modulates costly punishment only when unfair behavior was directed toward the participants and not when it was directed toward others. These findings provide neural and computational accounts of increased costly norm enforcement under adversity and advanced our understanding of the context-dependent nature of fairness preference.
© The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  computational modeling; costly norm enforcement; fMRI; fairness; ultimatum game

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Year:  2014        PMID: 24396005      PMCID: PMC4249466          DOI: 10.1093/scan/nst187

Source DB:  PubMed          Journal:  Soc Cogn Affect Neurosci        ISSN: 1749-5016            Impact factor:   3.436


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