Date on Master's Thesis/Doctoral Dissertation

1-2021

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Interdisciplinary and Graduate Studies

Degree Program

Interdisciplinary Studies with a specialization in Translational Neuroscience, PhD

Committee Chair

Depue, Brendan

Committee Co-Chair (if applicable)

Hindy, Nick

Committee Member

Hindy, Nick

Committee Member

Newton, Tamara

Committee Member

El-Mallakh, Rif

Committee Member

Magnuson, David

Committee Member

Corbitt, Cynthia

Author's Keywords

neuroscience: fmri; socioaffective; prosocial; empathy; emotion regulation

Abstract

Emotional Intelligence (EI) is a nebulous concept that permeates daily interpersonal communication. Despite prolific research into its benefits, EI subjective measurement is difficult, contributing to an enigmatic definition of its core constructs. However, neuroimaging research probing socioaffective brain mechanisms underlying putative EI constructs can add an objective perspective to existing models, thereby illuminating the nature of EI. Therefore, the primary aim of this dissertation is to identify brain networks underlying EI and examine how EI arises from the brain’s functional and structural neuroarchitecture. EI is first defined according to behavioral data, which suggests EI is made up of two core constructs: Empathy and Emotion Regulation (ER). The interaction of brain networks underlying Empathy and ER is then investigated using a novel neuroimaging analysis method: dynamic functional connectivity (dynFC). The results suggest efficient communication and (re)configuration between the CEN, DMN, SN underlie both ER and RME task dynamics, and that these temporal patterns relate to trait empathy and ER tendency. Given the demonstrated behavioral and neurobiological relationship between empathy and ER, our second aim is to examine each of these constructs individually through detailed experiments using a variety of neuroimaging methodologies. The dissertation concludes by proposing EI is an ability that arises from the effective, yet flexible communication between brain networks underlying Empathy and ER. The dissertation is divided into five chapters. Chapter I describes the foundational concept of EI as originally described by a variety of psychological figures and the lacuna that exists in terms of its neural correlates. Chapter II presents behavioral data that proposes EI is best predicted by Empathy and ER. Chapter III explores the dynamic relationship between brain networks underlying Empathy and ER, with the aim of elucidating their neurobiological associations, and investigate how such associations may combine to create EI. Chapter IV examines Empathy closely, by probing its neurobiological relationship to interoception and anxiety. Chapter V examines ER closely, by investigating whether gender plays a role in ER, and its neurobiological relationship to hormones. Chapter VI links the general findings from Chapters III, IV and V, and proposes an integrative neurocognitive EI model. The dissertation concludes by providing clinical and non-clinical applications for the model.

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