Triple Network Dynamic Functional Connectivity Predicts Everyday Repetitive Negative Thinking and Risk for Depression Recurrence

<p>Background: Repetitive negative thinking (RNT) is a vulnerability factor for major depressive disorder (MDD), but neural mechanisms that support resilience or recurrence after remission remain unclear. Guided by the triple-network model, we tested whether temporal dynamics of a theoretically adaptive state (characterized by low connectivity between the default mode network (DMN) and salience network (SN) and frontoparietal network (FPN) and high connectivity between SN and FPN) were associated with daily RNT, depression symptoms, and prospective MDD recurrence.Methods: Resting-state fMRI data were collected from 50 young adults with remitted MDD (rMDD) and 45 never-depressed controls. Group independent component analysis, sliding-window correlation and k-means clustering identified five recurring connectivity states. We related frequency and dwell time of the hypothesized triple-network state to ecological momentary assessment indices of RNT and depression symptom severity using linear regression, and to one-year MDD recurrence using Cox regression.Results: One of the five states demonstrated the hypothesized pattern: anticorrelation of DMN with SN and FPN, and positive SN-FPN coupling. More frequent occurrence in this state was associated with lower daily RNT across groups and lower depression symptom severity among participants with rMDD. In contrast, longer dwell time predicted increased risk of recurrence.Conclusions: Brief access to a triple-network state characterized by DMN segregation and SN-FPN coupling may index lower RNT and concurrent depression symptoms, whereas prolonged dwelling in the same state may mark recurrence vulnerability. These findings support decomposing state frequency and dwell time in dynamic functional connectivity models of MDD.</p>