Neural mediation of greed personality trait on economic risk-taking
Abstract
Dispositional greed, characterized by the insatiable hunger for more and the dissatisfaction for not having enough, has often been associated with heightened impulsivity and excessive risk-taking. Despite its far-reaching implications in social science and economics, however, the exact neural mechanisms of how greed personality influences risk-taking are still ill understood. In the present study, we showed the correlation between subjects' greed personality trait (GPT) scores and risk-taking was selectively mediated by individual's loss aversion, but not risk attitude. In addition, our neuroimaging results indicated that gain and loss prospects were jointly represented in the activities of the ventral striatum and medial orbitofrontal cortex (mOFC). Furthermore, mOFC responses also encoded the neural loss aversion signal and mediated the association between individual differences in GPT scores and behavioral loss aversion. Our findings provide a basis for understanding the specific neural mechanisms that mediates the effect of greed personality trait on risk-taking behaviors.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided in https://osf.io/rpve7/
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Neural mediation of greed personality trait on economic risk-takingOpen Science Framework, doi: 10.17605/OSF.IO/RPVE7.
Article and author information
Author details
Funding
National Natural Science Foundation of China (31421003)
- Jian Li
Ministry of Science and Technology of the People's Republic of China (2015CB559200)
- Jian Li
National Natural Science Foundation of China (31371019)
- Jian Li
The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Human subjects: All participants provided written informed consent. Study procedures were reviewed and approved by the Ethics Committee at Peking University (2017-11-01).
Copyright
© 2019, Li et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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