Endogenous event-related analysis reveals dynamic brain network reorganization abnormalities in depression

Current research on depression using electroencephalogram (EEG) microstates primarily focuses on static features of microstate sequences, such as duration and occurrence rate, which overlook dynamic transition processes reflecting rapid brain network reorganization. Additionally, traditional EEG acquisition paradigms relying on precise external events require patients to sustain attention to task events, resulting in excessive cognitive load and limiting their applicability in clinical diagnosis and intervention for depression. To address these dual challenges of insufficient capture of dynamic EEG features and limited clinical applicability, this study proposes an endogenous event-related analysis algorithm for the first time. This algorithm uses spontaneously occurring microstate transition events as endogenous markers, enabling dynamic EEG event-related analysis without requiring external event triggers. The method was validated on two independent public datasets (total sample size: 282). Results demonstrate that EEG microstate features exhibit consistency across datasets in both temporal and spatial dimensions, and the superimposed temporal signals associated with microstate transition events show significant cross-dataset correlations. Furthermore, analysis of depressive disorders indicates that patients with depression exhibit significant abnormal event-related synchronization or desynchronization in key brain regions (such as the occipital lobe, parietal lobe, temporal pole, supplementary motor area, limbic lobe) before and after specific microstate transition events compared to healthy subjects. Overall, the proposed endogenous event analysis algorithm and its revelation of transition-specific neural activity abnormalities in depression provide a methodological basis for developing closed-loop neurofeedback interventions targeting specific brain network state transitions, and establishes a new theoretical pathway for studying intrinsic brain dynamics.