Brain network dynamics during rumination relate to relapse of depression

Rumination is a maladaptive cognitive style and a risk factor for relapse of depression. However, the clinically relevant pattern of dynamic network reconfiguration during rumination in remitted depression and its implication in relapse remained unclear.

We employed a rumination induction neuroimaging paradigm in which subjects would be guided into an active rumination state and a distraction state. Forty-two patients with remitted depression were involved. Participants underwent assessments of rumination behavior and imaging tasks, and were then monitored for two year to assess the potential relapse of depression. A time-resolved community detection approach was applied to investigate the temporal dynamics of brain networks, and the dynamic network properties including flexibility and integration were analyzed.

Logistic regression revealed that higher rumination levels during remission increased the risk of depression relapse. Neuroimaging analyses demonstrated significantly reduced integration between the fronto-parietal network and dorsal attention network during rumination compared to distraction state (t(40) = -3.05, P_FDR = 0.036). Moreover, elastic net regression indicated that dynamic network features could predict two-year relapse outcomes with moderate accuracy (AUC = 0.70).

Our findings reveal a potential mechanistic link between the brain network dynamics during rumination and relapse of depression, shedding light on the intricate relationship between cognitive-affective processes, neural dynamics, and the potential vulnerability to depression recurrence.