Analysis of Dynamic Network Reconfiguration in First-Episode, Drug-Naive Patients with Major Depressive Disorder Based Multilayer Network

We collected resting-state fMRI data from 115 patients with major depressive disorder (MDD) and 120 healthy controls (HC). The GenLouvain community detection algorithm was performed to identify the temporal evolution of community in the multilayer network. Recruitment and integration coefficients were calculated according to the module allegiance matrix to quantify the dynamic characteristic of a node within each of the networks. We found aberrant recruitment and integration coefficients in MDD patients and their significant correlations with clinical scores, and such abnormally dynamic network reconfiguration provides a new perspective to explain the neurobiological characteristics of MDD patients.