Common and Disease-Specific EEG Microstate Alterations Across Alzheimer′s Disease, Parkinson′s Disease, Behavioral Variant Frontotemporal Dementia, and Multiple Sclerosis: A Cross-Disease Comparison

Abstract

Background

Alzheimer′s disease (AD), Parkinson′s disease (PD), behavioral variant frontotemporal dementia (bvFTD), and multiple sclerosis (MS) are common neurological disorders that disrupt brain networks and impair cognition and emotion. EEG microstates, as spatiotemporal markers of brain activity, have attracted increasing attention. They capture rapid large-scale brain dynamics on the millisecond timescale, offering a novel way to explore shared and distinct features across neurological disorders.

Methods

A total of 123 participants were included in this study, 35 with AD, 18 with bvFTD, 16 with PD, 22 with MS, and 32 healthy controls (HCs). High-density EEG signals were recorded during eyes-closed resting state. EEG microstate analysis was performed to extract duration, occurrence, and coverage for each microstate class. Group differences were examined using one-way ANOVA or Kruskal–Wallis tests, as appropriate.

Results

Compared with HC, patients with AD showed increased duration, occurrence, and coverage of Microstate C, and reduced occurrence and coverage of Microstate D. In PD, the duration of Microstate A was significantly reduced, whereas the occurrence and coverage of Microstate C were significantly elevated. The MS group showed partial differences relative to AD and PD, whereas no significant alterations were observed in bvFTD. Overall, Microstates C and D showed potential as cross-diagnostic electrophysiological biomarkers.

Conclusion

This study identified disorder-specific microstate alterations, with the most prominent differences in Microstates C and D. Notably, the divergence in Microstate D between AD and PD may reflect distinct mechanisms of network disruption. These findings provide new insights into the network-level pathophysiology of neurological disorders and highlight the promise of EEG microstates as transdiagnostic biomarkers for characterizing large-scale functional impairments.