DOI
https://doi.org/10.25772/J31P-5F94
Author ORCID Identifier
https://orcid.org/0000-0002-4786-1479
Defense Date
2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Clinical and Translational Sciences
First Advisor
F. Gerard Moeller
Abstract
Substance use disorders represent a major public health problem, and improved therapies are needed. There are therapies available for substance use disorders but not all patients benefit from those therapies. An improved understanding of the clinical neurobiology of addictions may help generate hypotheses for preclinical neurocircuit models of addiction and provide targets for neuromodulation which may help inform the development of future therapies. One tool that can help improve the understanding of the neurobiology of substance use disorders is resting state brain functional magnetic resonance imaging (fMRI). fMRI measurements taken at rest allow for the assessment of functional connectivity, or correlations in activity patterns between spatially distinct brain regions. Dynamic Causal Modeling-estimated effective (directional) connectivity further estimates the direction of connectivity between brain regions. As opposed to neuroscience models focused on specific brain regions acting as independent modules, recent research has emphasized the analysis of the brain as functional networks of brain regions (Bressler & Menon, 2010). Functional and effective connectivity can provide insight into how the brain is organized into networks and how those networks may be different in substance use disorders compared to non-drug users. The study of how brain networks interact opens a new avenue of research on the neurobiology of substance use disorders and other related brain disorders. However, published studies assessing functional or effective connectivity among whole brain networks in substance use disorders compared to non-drug using controls are lacking. Additionally, there has been a relative lack of studies assessing functional or effective connectivity of the executive control network, despite well documented executive control deficits in substance use disorders. Robust and replicable within- and between-network connectivity differences in substance use disorders could help generate hypotheses for preclinical neuroscience models of addiction and provide targets for neuromodulation studies in substance use disorder subjects. The present studies aimed to assess within- and between-network brain functional connectivity and effective connectivity among three key brain networks (Salience Network (SN), Default Mode Network (DMN), and the Executive Control Networks (left ECN (LECN) and right ECN (RECN))) in opioid use disorder (OUD) subjects and cocaine dependent (CD) subjects compared to non-drug using healthy control subjects (HC). The present work found weaker functional connectivity within the LECN in OUD relative to HC. The present work also found strong evidence for group differences in RECN to LECN effective connectivity in CD relative to HC when tobacco use was controlled for and associations between RECN and LECN effective connectivity and delay discounting, tobacco use, and recent drug use in both the CD vs. HC comparison and OUD vs. HC comparison. These results provide evidence that RECN and LECN effective connectivity may relate to multiple factors associated with addiction. RECN and LECN effective connectivity should be further studied in preclinical, neuromodulation, and treatment studies in addiction.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-11-2023