Neural correlates of proposers’ fairness perception in punishment and non-punishment economic games
Autor: | Yuanhong Wu, Ganping Ma, Jing Zhang, Xiaolei Zhu, Mingliang Chen |
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Rok vydání: | 2019 |
Předmět: |
Neural correlates of consciousness
Ultimatum game media_common.quotation_subject 05 social sciences 050109 social psychology 050105 experimental psychology Dictator game Feeling Perception 0501 psychology and cognitive sciences Norm (social) Psychology Social psychology General Psychology media_common |
Zdroj: | Current Psychology. 40:1838-1849 |
ISSN: | 1936-4733 1046-1310 |
DOI: | 10.1007/s12144-019-0129-3 |
Popis: | In economic games, people acting as responders always hope to be treated fairly; otherwise they may punish proposers even sacrificing own monetary gains. However, people often treat others unequally when they become proposers, especially in the absence of punishment mechanisms. Will people lose fairness perception when they become proposers? Previous researches mainly focused on the fairness perception of responders, few paid attentions to that of proposers. In present study, we used event-related potentials (ERPs) to record the neural activities of participants acting as proposers in the ultimatum game and the dictator game, corresponding to punishment condition and non-punishment condition respectively. In each trial, a participant could choose an offer from three categories: absolutely unfair, relatively unfair and fair. Behavioral results indicate that the proposers would choose more highly unfair offers that are beneficial to themselves in a non-punishment condition than in a punishment condition. However, no matter whether there was punishment mechanism, more highly unfair offers elicited larger MFN. This finding may reflect the existence of the proposers’ unfairness aversion and guilty feeling triggered by intentional violations of social fairness norm and shows that the proposers do not give up the fairness norm in the cockles of the heart even in a non-punishment environment. |
Databáze: | OpenAIRE |
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