Disrupted Functional Connectivity in the Frontal-subcortical Network as a Vulnerability Factor for Depression in Multiple Sclerosis
Open Access
- Author:
- Vargas, Gray Alexandra
- Graduate Program:
- Psychology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- June 17, 2013
- Committee Members:
- Peter Andrew Arnett, Dissertation Advisor/Co-Advisor
Frank Gerard Hillary, Committee Member
Stephen Jeffrey Wilson, Committee Member
Lisa Michelle Kopp, Special Member - Keywords:
- multiple sclerosis
depression
functional connectivity
stress
social support - Abstract:
- Multiple Sclerosis (MS) is a chronic demyelinating disease that also causes widespread atrophy, inflammation, and other damage, and thus is a disease that affects neural connectivity. Depression prevalence in MS is high, but the etiology is not well understood. A specific group of brain regions, the frontal-subcortical network, has consistently been shown to be related to depression in the general population. The MS population thus represents a unique opportunity to study how neuropathology might disrupt networks in the brain and make individuals with MS more vulnerable to depression, especially if they also experience psychosocial stressors and have low social support. Twenty-five individuals with MS completed a functional MRI scan while performing an emotional face matching task, and also completed several self-report measures. Unified structural equation models were generated using a Group Iterative Multiple Model Estimation program to examine effective connectivity during affective and neutral trials. Data were analyzed at the individual and group level, as well as by comparing high and low depression group models. Several connectivity measures were found to relate to depression symptoms and depression proneness. On the individual level, fewer subcortical to cortical paths during affective trials and more cortical to subcortical paths during neutral trials were associated with depression. When comparing high versus low depression group models, the high depression group had fewer connections between the dorsolateral prefrontal cortex (dlPFC) and subcortical regions and fewer cortical to subcortical paths during affective trials, and fewer cortical-subcortical paths, fewer cortical to subcortical paths, and increased subgenual anterior cingulate cortex (sgACC)-amygdala connectivity during neutral trials. Furthermore, several of these connectivity measures interacted with psychosocial variables to predict depression. For some interactions, lower connectivity in this network interacted with higher stress to predict depression. However, for some measures, especially during neutral trials, increased connectivity was associated with increased depression symptoms, especially if associated with higher stressors. This study demonstrates the feasibility of testing effective connectivity in an MS population and shows that there are meaningful differences in connectivity that relate to depression in this group. More studies are necessary to better understand the direction of these effects, the differences in connectivity during emotional and non-emotional processing, and the nature of the interaction with psychosocial variables.