Psychology ETDs

Publication Date

Spring 4-17-2017

Abstract

Although research finds that brain abnormalities during moral decisions underlie traits that lead to crime, understanding of these neural dynamics is limited. Here we use two samples to explore the role network engagement and components during moral processing. We used independent component analysis and functional network connectivity analysis to examine hemodynamic response during an fMRI task of moral processing. Eighty-four community and 539 incarcerated adult men and women participated; MANCOVA and machine learning algorithms were used to identify individual and group differences in both samples. We found patterns of neural engagement and connectivity consistent with proposed models of moral cognition and that age, IQ, and sex moderated neural engagement and connectivity during moral cognition in regions including the temporoparietal junction and prefrontal cortex. We also found that incarcerated individuals differed from community controls on functional network connectivity and dynamism during moral processing and that psychopathic traits were related to network engagement in regions including the temporoparietal junction, cingulate, and temporal poles. These results extend the literature on moral processing to functional network dynamics, as well as highlighting the need to consider individual differences in understanding the neural underpinnings of moral processing. Finally, this study provides evidence that neural connectivity during moral processing may be able to predict criminality, although follow-up research on prospective prediction is necessary.

Degree Name

Psychology

Level of Degree

Doctoral

Department Name

Psychology

First Committee Member (Chair)

Kent Kiehl

Second Committee Member

Vince Calhoun

Third Committee Member

Vince Clark

Fourth Committee Member

Jim Cavanagh

Fifth Committee Member

Carla Harenski

Sponsors

NIH

Language

English

Keywords

moral, FNC, ICA, fMRI, psychopathy, forensic

Document Type

Dissertation

Share

COinS