Resting-state network alterations in depression: a comprehensive meta-analysis of functional connectivity

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Depression is associated with disruptions in resting-state networks (RSNs).
• Previous findings on RSN connectivity in depression are inconsistent, hindering understanding of underlying neurobiology.
• This study addresses inconsistencies by systematically analyzing RSN alterations in depression.

Purpose of the Study:

• To comprehensively characterize alterations in resting-state network (RSN) connectivity in depression.
• To elucidate the neurobiological mechanisms underlying depression through RSN analysis.
• To synthesize findings from multiple studies on RSN disruptions in depression.

Main Methods:

• Systematic literature search of PubMed and Web of Science for resting-state fMRI studies in depression.
• Inclusion of studies using seed-based connectivity or independent component analysis.
• Performance of coordinate-based meta-analyses to assess within- and between-network RSN alterations.

Main Results:

• Analysis of 58 studies (2321 patients, 2197 controls) revealed significant RSN connectivity alterations in depression.
• Within-network changes included altered default mode network (DMN) and increased frontoparietal network (FPN) connectivity.
• Between-network findings showed increased DMN-FPN and limbic network (LN)-DMN connectivity, among other alterations; illness duration correlated with VAN-DAN connectivity.

Conclusions:

• This meta-analysis provides a detailed characterization of RSN disruptions in depression.
• Findings enhance the understanding of the neurobiological underpinnings of depression.
• Identified RSN alterations offer potential targets for future research and therapeutic interventions.