Altered EEG microstate dynamics as a neurophysiological biomarker for diagnostic differentiation in Schizophrenia

Background: To examine spatiotemporal modifications in electroencephalogram (EEG) microstates among individuals diagnosed with schizophrenia utilizing a five-class model, and to evaluate the potential of microstate parameters as diagnostic biomarkers. Methods: Resting-state EEG data were collected from 122 patients with schizophrenia and 72 age-and sex-matched healthy controls. EEG recordings were preprocessed and analyzed using a standardized pipeline, applying a five-class microstate framework (A-E). Temporal parameters, transition probabilities, and spatial topographies were quantified. Group comparisons were conducted, and the diagnostic utility of microstate features was evaluated using receiver operating characteristic analysis. The study also investigated the correlations between various microstate metrics and the severity of symptoms, as measured by Positive and Negative Syndrome Scale (PANSS) scores. Results: Significant differences were observed across all five microstate classes between the groups. Patients with schizophrenia showed shorter durations and increased occurrences of all microstates, altered transition patterns, and altered topographic distributions. Notably, reduced duration of microstate A, associated with auditory and linguistic processing, demonstrated the strongest discriminatory power, with an AUC of 0.93, sensitivity of 93.1 %, and specificity of 83.6 %. Despite allowing for group discrimination, microstate metrics were not significantly correlated with symptom severity as measured by the PANSS within the group of patients with schizophrenia. Conclusions: This study presents robust evidence of disrupted EEG microstate dynamics in patients with schizophrenia. The reduced duration of microstate A may serve as a potential neurophysiological biomarker, independent of symptom severity, for diagnostic differentiation purposes.