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Money talks: neural substrate of modulation of fairness by monetary incentives.

Zhou Y, Wang Y, Rao LL, Yang LQ, Li S - Front Behav Neurosci (2014)

Bottom Line: We found evidence for a significant modulation by the proposed amount on fairness in the right lateral prefrontal cortex (PFC) and the bilateral insular cortices.Inter-individual differences in the modulation effects in the left inferior frontal gyrus (IFG) accounted for inter-individual differences in the behavioral modulation effect as measured by the rejection rate, supporting the concept that the PFC plays a critical role in making fairness-related normative decisions in a social interaction condition.Our findings provide neural evidence for the modulation of fairness by monetary incentives as well as accounting for inter-individual differences.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Behavioral Science, Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences Beijing, China.

ABSTRACT
A unique feature of the human species is compliance with social norms, e.g., fairness, even though this normative decision means curbing self-interest. However, sometimes people prefer to pursue wealth at the expense of moral goodness. Specifically, deviations from a fairness-related normative choice have been observed in the presence of a high monetary incentive. The neural mechanism underlying this deviation from the fairness-related normative choice has yet to be determined. In order to address this issue, using functional magnetic resonance imaging we employed an ultimatum game (UG) paradigm in which fairness and a proposed monetary amount were orthogonally varied. We found evidence for a significant modulation by the proposed amount on fairness in the right lateral prefrontal cortex (PFC) and the bilateral insular cortices. Additionally, the insular subregions showed dissociable modulation patterns. Inter-individual differences in the modulation effects in the left inferior frontal gyrus (IFG) accounted for inter-individual differences in the behavioral modulation effect as measured by the rejection rate, supporting the concept that the PFC plays a critical role in making fairness-related normative decisions in a social interaction condition. Our findings provide neural evidence for the modulation of fairness by monetary incentives as well as accounting for inter-individual differences.

No MeSH data available.


Related in: MedlinePlus

Mean rejection rates as a function of proposal fairness for different stake sizes (A), proposer types (B), and the interaction among these three factors (C). Error bars indicate standard errors of the mean.
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Figure 2: Mean rejection rates as a function of proposal fairness for different stake sizes (A), proposer types (B), and the interaction among these three factors (C). Error bars indicate standard errors of the mean.

Mentions: The rejection rate was investigated by a repeated measures ANOVA, exploring the main effects of fairness (50%, 20%), proposer type (human, computer), stake size (high, low), and the interaction between these factors. Mauchly's test of sphericity showed that the sphericity assumption was met (all ps > 0.05). Significant main effects of fairness [F(1, 27) = 65.34, p < 0.001, partial η2 = 0.708], stake size [F(1, 27) = 7.43, p = 0.011, partial η2 = 0.216] and proposer type [F(1, 27) = 18.22, p < 0.001, partial η2 = 0.403] were found. These main effects separately indicated that unfair proposals (M = 0.47, SD = 0.28) were more often rejected than fair ones (M = 0.05, SD = 0.07), proposals from humans (M = 0.34, SD = 0.18) were more often rejected than those from computers (M = 0.18, SD = 0.17), and proposals with a low stake size (M = 0.31, SD = 0.17) were more often rejected than those with a high stake size (M = 0.21, SD = 0.17). The interaction between fairness and stake size was significant [F(1, 27) = 8.68, p = 0.007, partial η2 = 0.243]. A post-hoc pairwise least significant difference (LSD) test indicated that when the proposals were unfair, the rejection rates for proposals with a low stake size (M = 0.56, SD = 0.31) were significantly higher than those for proposals with a high stake size (M = 0.38, SD = 0.33) (Figure 2A). The interaction between fairness and proposer type was also significant [F(1, 27) = 13.52, p = 0.001, partial η2 = 0.334]. A post-hoc pairwise LSD test indicated that the rejection rates for proposals from human partners (M = 0.60, SD = 0.32) were significantly higher than those for proposals from computer partners (M = 0.34, SD = 0.33) when the proposals were unfair (Figure 2B). There were no significant differences in rejection rates when the proposals were fair for these interactions. No significant interaction between stake size and proposal type was found. There was a trend toward significance in interaction among the three factors [F(1, 27) = 3.09, p = 0.09, partial η2 = 0.103]. A post-hoc analysis revealed that the rejection rate for the unfair proposals with a high stake size was lower than that for the unfair proposals with a low stake size in the human condition (p = 0.012), whereas this difference only showed a trend toward significance in the computer condition (p = 0.062). In addition, we found no differences between the rejection rate for the fair proposal with a high stake size and that for the fair proposal with a low stake size in either the human condition or the computer condition (ps > 0.05) (Figure 2C).


Money talks: neural substrate of modulation of fairness by monetary incentives.

Zhou Y, Wang Y, Rao LL, Yang LQ, Li S - Front Behav Neurosci (2014)

Mean rejection rates as a function of proposal fairness for different stake sizes (A), proposer types (B), and the interaction among these three factors (C). Error bars indicate standard errors of the mean.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4017157&req=5

Figure 2: Mean rejection rates as a function of proposal fairness for different stake sizes (A), proposer types (B), and the interaction among these three factors (C). Error bars indicate standard errors of the mean.
Mentions: The rejection rate was investigated by a repeated measures ANOVA, exploring the main effects of fairness (50%, 20%), proposer type (human, computer), stake size (high, low), and the interaction between these factors. Mauchly's test of sphericity showed that the sphericity assumption was met (all ps > 0.05). Significant main effects of fairness [F(1, 27) = 65.34, p < 0.001, partial η2 = 0.708], stake size [F(1, 27) = 7.43, p = 0.011, partial η2 = 0.216] and proposer type [F(1, 27) = 18.22, p < 0.001, partial η2 = 0.403] were found. These main effects separately indicated that unfair proposals (M = 0.47, SD = 0.28) were more often rejected than fair ones (M = 0.05, SD = 0.07), proposals from humans (M = 0.34, SD = 0.18) were more often rejected than those from computers (M = 0.18, SD = 0.17), and proposals with a low stake size (M = 0.31, SD = 0.17) were more often rejected than those with a high stake size (M = 0.21, SD = 0.17). The interaction between fairness and stake size was significant [F(1, 27) = 8.68, p = 0.007, partial η2 = 0.243]. A post-hoc pairwise least significant difference (LSD) test indicated that when the proposals were unfair, the rejection rates for proposals with a low stake size (M = 0.56, SD = 0.31) were significantly higher than those for proposals with a high stake size (M = 0.38, SD = 0.33) (Figure 2A). The interaction between fairness and proposer type was also significant [F(1, 27) = 13.52, p = 0.001, partial η2 = 0.334]. A post-hoc pairwise LSD test indicated that the rejection rates for proposals from human partners (M = 0.60, SD = 0.32) were significantly higher than those for proposals from computer partners (M = 0.34, SD = 0.33) when the proposals were unfair (Figure 2B). There were no significant differences in rejection rates when the proposals were fair for these interactions. No significant interaction between stake size and proposal type was found. There was a trend toward significance in interaction among the three factors [F(1, 27) = 3.09, p = 0.09, partial η2 = 0.103]. A post-hoc analysis revealed that the rejection rate for the unfair proposals with a high stake size was lower than that for the unfair proposals with a low stake size in the human condition (p = 0.012), whereas this difference only showed a trend toward significance in the computer condition (p = 0.062). In addition, we found no differences between the rejection rate for the fair proposal with a high stake size and that for the fair proposal with a low stake size in either the human condition or the computer condition (ps > 0.05) (Figure 2C).

Bottom Line: We found evidence for a significant modulation by the proposed amount on fairness in the right lateral prefrontal cortex (PFC) and the bilateral insular cortices.Inter-individual differences in the modulation effects in the left inferior frontal gyrus (IFG) accounted for inter-individual differences in the behavioral modulation effect as measured by the rejection rate, supporting the concept that the PFC plays a critical role in making fairness-related normative decisions in a social interaction condition.Our findings provide neural evidence for the modulation of fairness by monetary incentives as well as accounting for inter-individual differences.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Behavioral Science, Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences Beijing, China.

ABSTRACT
A unique feature of the human species is compliance with social norms, e.g., fairness, even though this normative decision means curbing self-interest. However, sometimes people prefer to pursue wealth at the expense of moral goodness. Specifically, deviations from a fairness-related normative choice have been observed in the presence of a high monetary incentive. The neural mechanism underlying this deviation from the fairness-related normative choice has yet to be determined. In order to address this issue, using functional magnetic resonance imaging we employed an ultimatum game (UG) paradigm in which fairness and a proposed monetary amount were orthogonally varied. We found evidence for a significant modulation by the proposed amount on fairness in the right lateral prefrontal cortex (PFC) and the bilateral insular cortices. Additionally, the insular subregions showed dissociable modulation patterns. Inter-individual differences in the modulation effects in the left inferior frontal gyrus (IFG) accounted for inter-individual differences in the behavioral modulation effect as measured by the rejection rate, supporting the concept that the PFC plays a critical role in making fairness-related normative decisions in a social interaction condition. Our findings provide neural evidence for the modulation of fairness by monetary incentives as well as accounting for inter-individual differences.

No MeSH data available.


Related in: MedlinePlus