State-specific alterations in dynamic functional network connectivity in Wilson’s disease: a resting-state fMRI study

Background Dynamic functional network connectivity (dFNC) may reveal time-varying brain network abnormalities in Wilson’s disease (WD) that are not captured by static analyses. We aimed to characterize static and dynamic large-scale network connectivity in WD using resting-state fMRI.Methods This retrospective study included 32 patients with WD and 32 healthy controls. Group independent component analysis identified eight components representing seven resting-state networks. Static connectivity was assessed across the full scan, while dynamic states were identified using sliding-window correlation and k-means clustering. State-specific connectivity and temporal metrics were compared between groups, and clinical associations were explored using Spearman correlation analyses.Results No sFNC difference survived false discovery rate correction. dFNC revealed group differences in States 2 and 4. In State 2, patients with WD showed increased default mode network (DMN)-left frontoparietal network connectivity and decreased DMN-dorsal attention network (DAN) and DMN-sensorimotor network connectivity. In State 4, DMN-left frontoparietal network and DAN-visual network connectivity increased, whereas DAN-right frontoparietal network connectivity decreased. Patients with WD also had shorter MDT in State 2, which correlated positively with blood urea nitrogen levels (Spearman’s r = 0.478, FDR-corrected p = 0.035).Conclusion WD showed state-specific changes in dynamic brain network connectivity that were not detected by static analysis. The correlation between State 2 MDT and blood urea nitrogen may reflect a relationship between brain network dynamics and peripheral metabolic status.