Functional Connectivity Changes in Major Depressive Disorder

Abstract

Major depressive disorder (MDD) is associated with brain-wide network disruptions. This study investigates a large resting-state functional magnetic resonance imaging dataset (N = 519) to analyze static and dynamic functional network connectivity (FNC). Using independent component analysis, our analysis revealed hyperconnectivity within sensorimotor and temporal subdomains, hypoconnectivity from higher cognitive networks, and hyperconnectivity from the default mode and sensorimotor domains in MDD. A novel frequency-sensitive dynamic approach identified disruptions in the temporal synchrony of brain states engaging the default mode-paralimbic, sensorimotor, and frontal regions, as well as the subcortical limbic, frontal, and salience regions. Overall, the findings highlight the utility of combining static and dynamic approaches in large neuroimaging datasets to elucidate the neural underpinnings of MDD pathology.