Analysis of microstate features for Parkinson's disease based on reliability validation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Clinical Neurology

Background:

• Parkinson's disease (PD) is characterized by abnormal brain activity, but objective indicators for progression are lacking.
• Assessing brain activity changes presents a potential avenue for monitoring PD.
• Current methods for evaluating PD progression lack objective biomarkers.

Purpose of the Study:

• To determine the optimal epoch duration for reliable electroencephalogram (EEG) microstate analysis in PD.
• To investigate alterations in EEG microstate features in PD patients.
• To explore the correlation between microstate features and clinical assessments of PD severity.

Main Methods:

• Assessed the reliability of EEG microstate topography and temporal features across different epoch durations in PD and healthy controls.
• Selected reliable EEG epochs (≥3 minutes) for microstate analysis.
• Correlated identified microstate features with clinical scales (MoCA, UPDRS).

Main Results:

• EEG microstate analysis demonstrated high reliability for epoch durations of 3 minutes and above.
• Significant differences in microstate D topology and microstates C and D temporal features were observed in PD patients compared to controls.
• Microstate C occurrence correlated negatively with MoCA scores, and microstate D duration correlated positively with UPDRS scores.

Conclusions:

• A minimum EEG epoch duration of 3 minutes is recommended for reliable microstate analysis in PD.
• EEG microstate analysis provides a reliable method for detecting PD-related brain activity changes.
• Microstate features show potential as objective indicators for evaluating Parkinson's disease progression in clinical settings.