ArticleBrain and behavior2026
Altered Dynamic Functional Connectivity of the Frontoparietal Network in Major Depressive Disorder: Evidence From a Large-Scale Resting-State fMRI Study.
Article in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- The spectrum of neurodevelopmental disorders: comorbidities as clues to pathogenesis.Current opinion in psychiatry · 2026Review
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Abstract
Major depressive disorder (MDD) is a prevalent psychiatric condition characterized by affective disturbances and cognitive deficits. Among these, cognitive inflexibility and executive dysfunction are particularly prominent, yet the temporal dynamics of the frontoparietal control network (FPN), a core substrate of cognitive control, remain poorly understood. Using harmonized resting-state fMRI data from the REST-meta-MDD consortium (n = 887; 442 MDD, 445 healthy controls), we investigated dynamic functional connectivity (dFC) within the FPN. Time-varying correlations among 21 FPN nodes were estimated using a sliding-window approach and clustered via k-means to identify recurring connectivity states. Temporal metrics included fractional occupancy, mean dwell time, and transition counts. Three unique FPN states were recognized. In comparison to healthy individuals, those with MDD exhibited prolonged durations in a hypoconnected state, extended dwell times in this configuration, and fewer total transitions, indicating diminished neural flexibility. Direct transitions between low-connectivity (hypoconnected) and high-connectivity (hyperconnected) states were selectively diminished, indicating a disruption in the direct transition between two functionally distinct states of the FPN. Overall, these findings reveal a fundamental disruption in the temporal organization of frontoparietal connectivity in MDD, marked by predominant hypoconnectivity, reduced flexibility, and constrained state transitions. By delineating the dynamic properties of network function, this study advances a mechanistic framework for interpreting prior inconsistencies in static connectivity research and underscores the necessity of time-resolved approaches in characterizing large-scale network dysfunction in psychiatric disorders.
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