Date of Award

2018

Document Type

Dissertation

Degree Name

Master of Biomedical Science

Department

Pharmacology

College

College of Graduate Studies

First Advisor

Jane Joseph

Second Advisor

Joe B. Blumer

Third Advisor

Thomas Jhou

Fourth Advisor

Andrew Lawson

Fifth Advisor

Thomas Naselaris

Abstract

The neurobiological basis of individual differences in personality is still poorly understood. Previous research has previously linked personality traits to risk factors for developing mental illness or engaging in high-risk behavior. Previous research has also linked personality traits to individual differences in resting state functional connectivity, which describes regional interactions in the brain when a person is not engaged in an active task. This study aimed to apply a theory of personality derived from behavioral neuroscience and ethology known as Reinforcement Sensitivity Theory (RST) to the characterization of brain networks underlying personality. RST defines four motivational systems in the brain, the Behavioral Approach System (BAS), Behavioral Inhibition System (BIS), Fight-Flight- Freeze System (FFFS), and Executive Control System (ECS) which enable learning from and responding to current environmental demands. Individual variation in the functioning of these motivational systems creates different propensities to seek out rewarding stimuli and avoid potentially threatening ones, corresponding to the ubiquitous presence of reward and punishment sensitivity related traits across personality models. However, RST has not been applied to characterizing the relationship of brain development to the maturation of personality and the relationship of the RST systems to resting state networks. Understanding how these circuits change developmentally from adolescence to adulthood is vital to identify how high-risk personality traits become stable parts of adult personality. In this study, 25 adolescents and 52 adults each completed a battery of personality assessments and a six minute resting state fMRI scan. It was hypothesized that a factor analysis of each personality trait would reveal factors corresponding to the RST motivational systems. For each participant factor scores were computed corresponding to these traits. Network analysis was completed using a graph theory approach to characterize important nodes in the brain. Following this, an a priori set of brain regions derived from RST was used for a regression analysis to test the hypothesis that nodes within the RST systems would predict the corresponding personality trait. The results support the notion that important resting state network nodes within the RST systems correspond to personality traits. The results also suggest that these networks are established during adolescence and change little into young adulthood, with the exception of the ECS. Therefore, early intervention to teach adaptive coping skills and behaviors is desirable to ameliorate the potential life outcomes of high-risk personality traits for drug abuse or mood disorders.

Rights

All rights reserved. Copyright is held by the author.

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