Dynamic community structure in major depressive disorder: A resting-state MEG study

Background: Major Depressive Disorder (MDD), characterized by depressed mood or anhedonia, is associated with altered functional connectivity (FC) within and between large scale networks such as the Default Mode Network (DMN), the Central Executive Network (CEN) and the Salience Network (SN). Since aberrant FC exhibits temporal variability and could give rise to distorted reconfiguration of functional brain networks, an in-depth analysis of the community structure could provide further insight into the synchrony of networks. We hypothesized that alterations in dynamic network community structure in MDD could be temporally accompanied by disrupted conscious states of these three networks. Methods: 26 MDD patients and 25 healthy controls were scanned using a whole-head resting-state Magnetoencephalography (MEG) machine. A novel multilayer modularity framework explored the functional modulation of these networks. Recruitment (R) and integration (I) provided the strength of interaction within networks or across networks, respectively. Results: The brain regions in the DMN, CEN and SN were transiently integrated and segmented in both patients and controls. R of CEN and I of SN were significantly greater in MDD compared to controls. Conclusion: Intrinsic resting-state networks dynamically interact and reorganize into distinct functional modules in both patients and controls. However, the CEN hyper-intertwines with itself and SN hyper-integrates among the network of interest in depressed patients compared to controls. Network-level alterations in R and I revealed a more generalized system-level effect rather than a focal-wise effect from a neural dynamic perspective. This could potentially highlight an abnormal network-based mechanism in depression.