Whole-Brain Functional Dynamics Track Depressive Symptom Severity. (29th March 2021)

• Record Type: Journal Article
• Authors: Goodman, Zachary T; Bainter, Sierra A; Kornfeld, Salome; Chang, Catie; Nomi, Jason S; Uddin, Lucina Q
• Is Part Of: Cerebral cortex. Volume 31:Number 11(2021)
• Page Start: 4867
• Page End: 4876
• Publication Date: 2021-03-29
• Subjects: brain network dynamics -- coactivation pattern analysis -- depressive symptoms -- medial frontoparietal network -- resting state fMRI; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhab047
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Depressive symptoms are reported by 20% of the population and are related to altered functional integrity of large-scale brain networks. The link between moment-to-moment brain function and depressive symptomatology, and the implications of these relationships for clinical and community populations alike, remain understudied. The present study examined relationships between functional brain dynamics and subclinical-to-mild depressive symptomatology in a large community sample of adults with and without psychiatric diagnoses. This study used data made available through the Enhanced Nathan Kline Institute-Rockland Sample; 445 participants between 18 and 65 years of age completed a 10-min resting-state functional MRI scan. Coactivation pattern analysis was used to examine the dimensional relationship between depressive symptoms and whole-brain states. Elevated levels of depressive symptoms were associated with increased frequency and dwell time of the default mode network, a brain network associated with self-referential thought, evaluative judgment, and social cognition. Furthermore, increased depressive symptom severity was associated with less frequent occurrences of a hybrid brain network implicated in cognitive control and goal-directed behavior, which may impair the inhibition of negative thinking patterns in depressed individuals. These findings demonstrate how temporally dynamic techniques offer novel insights into time-varying neural processes underlying subclinical and clinically meaningful depressive symptomatology.