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Individualized Prediction of Third-Party Punishment Behavior from Intrinsic Functional Brain Connectivity

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dc.contributor.advisor Krueger, Frank
dc.contributor.author Hsu, Ko-Tsung
dc.creator Hsu, Ko-Tsung
dc.date 2019-04-25
dc.date.accessioned 2019-07-01T20:47:28Z
dc.date.available 2019-07-01T20:47:28Z
dc.identifier.uri https://hdl.handle.net/1920/11483
dc.description.abstract A robust human society is developed normally on the ground of social cooperation, serving a critical role in human relationships. Importantly, social cooperation is subjected to the establishment of social norms. To maintain human society, third-party punishment (TPP) as a consistently sanctioning behavior facilitates the enforcement of social norms. At the psychological level, TPP is based on blame which is an amalgam of intent and harm to victim and the offender’s intention in violating social norms. At the neural level, TPP behavior builds on the interaction of the salience network (determining the degree of norm violation), default-mode network (determining the degree of blame), and central-executive network (determining the degree of punishment). Although task-based functional magnetic resonance imaging (fMRI) has been extensively used to investigate individual differences in the propensity to punish, whether TPP behavior can be predicted through task-free fMRI based on resting-state functional connectivity (RSFC) remains open. The goal of this study was to apply multivariate prediction analysis (MVPA) to RSFC patterns of large-scale ix brain networks to predict individual difference in TPP behavior measured with a TPP exchange game. The findings demonstrated that RSFC between the default-mode network (DMN) and the central-executive network (CEN) predicted TPP behavior, indicating a signal transmission from blame (DMN) to punishment behavior (CEN). In conclusion, investigating the individual difference in TPP behavior based on RSFC provides us with a new comprehensive understanding of sustaining cooperation and enforcement of social norms in human society.
dc.language.iso en en_US
dc.subject resting-state functional connectivity en_US
dc.subject third-party punishment en_US
dc.subject economic game en_US
dc.subject multivariate prediction analysis en_US
dc.subject brain connectivity en_US
dc.subject social norm en_US
dc.title Individualized Prediction of Third-Party Punishment Behavior from Intrinsic Functional Brain Connectivity en_US
dc.type Thesis en_US
thesis.degree.name Master of Science in Bioinformatics en_US
thesis.degree.level Master's en_US
thesis.degree.discipline Bioinformatics en_US
thesis.degree.grantor George Mason University en_US


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