Review of EEG microstate analysis shows high diagnostic accuracy for distinguishing neuropsychiatric symptoms from cognitive impairment

Objectives: Neuropsychiatric symptoms (NPS) are prevalent in individuals of cognitive impairement (CI). However, the similarities and disparatenesses in whole-brain dynamics between individuals of CI and NPS are controversy. Electroencephalography (EEG) microstates reflect the whole-brain dynamics. This study aimed to investigate the differential EEG microstates parameters between CI and NPS and to construct related diagnostic model. Methods/design: This study was a cross-sectional study. Clinical and EEG data were collected, and an EEG microstate analysis were performed. The Least absolute shrinkage and selection operation (LASSO) regression model was used to identify significant differential EEG microstates parameters between CI and NPS and to construct a diagnostic model. The model performance was tested by the receiver operating characteristic curve (ROC). Results: This study enrolled 78 participants. A total of 36 EEG microstates parameters were identified and included in the differential analysis. In the LASSO regression model, 4 significant differential EEG microstates parameters were selected, including the duration of class C, TPAB, TPBA, and TPDC. The ROC results showed that the diagnostic model for distinguishing NPS patients from CI patients achieved an area under the curve (AUC) of 0.905(95% CI: 0.784-1.000) , with a sensitivity of 100.0% and a specificity of 76.9%. Conclusions: The diagnostic model based on EEG microstate parameters showed a good performance for differentiating NPS patients from CI patients.