Resting-state dynamic functional connectivity in major depressive disorder: A systematic review

Area of Science:

• Neuroscience
• Psychiatry
• Network Science

Background:

• Traditional static functional connectivity has limitations in understanding dynamic brain network alterations in major depressive disorder (MDD).
• A comprehensive review of dynamic functional connectivity (dFC) in MDD is lacking.
• dFC offers novel insights into the transient interactions within and between brain networks.

Purpose of the Study:

• To review and synthesize existing literature on the pathological mechanisms of MDD using dFC.
• To explore how dFC reveals abnormalities in brain regions, networks, states, and topological properties in MDD.
• To assess the potential of dFC in the clinical diagnosis and treatment of MDD.

Main Methods:

• Systematic review of 45 eligible studies on MDD and dFC.
• Analysis of findings related to brain regions, functional networks, brain states, and topological properties.
• Evaluation of dFC's role in recognition and longitudinal studies of MDD.

Main Results:

• Consistent findings implicate the default-mode network (DMN) and its subregions in MDD pathology.
• MDD is associated with impaired large-scale network integrity, inter-network imbalance, and prolonged weakly-connected states, particularly involving the DMN.
• Abnormal state transition frequencies correlate with MDD severity, and incorporating dynamic properties enhances diagnostic recognition.

Conclusions:

• dFC provides valuable insights into the non-stationary nature of aberrant brain activity in MDD patients.
• dFC enhances the recognition effect for MDD when integrated into topological network metrics.
• This review highlights dFC's potential for clinical diagnosis and treatment, offering new perspectives on MDD's neurobiological mechanisms.