Large-Scale Network Dysfunction in Major Depressive Disorder

Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive.

To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. DATA SOURCES: Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. STUDY SELECTION: Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. DATA EXTRACTION AND SYNTHESIS: Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network.