Abstract
BACKGROUND AND HYPOTHESIS: Identifying reliable diagnostic biomarkers in catatonia remains a key challenge to improve early intervention and reduce morbidity and mortality. Since its pathophysiology may involve cortical dysconnectivity, electroencephalography (EEG) could provide accessible disease-associated measures, such as power spectral density (PSD), peak alpha frequency (PAF), and C and D microstates. However, EEG is yet to be used for this purpose. STUDY DESIGN: This study is a case-control retrospective transdiagnostic hospital-based cohort. We analyzed resting-state EEG data from patients diagnosed with schizophrenia or mood disorders, both with (n = 102) and without (n = 519) catatonia. Linear regression models assessed associations between catatonia status and PSD, PAF, and microstates, adjusting for age, sex, medication (computed as olanzapine, fluoxetine, and diazepam equivalents), and comorbid neurodevelopmental or neurological conditions. STUDY RESULTS: Patients with catatonia showed increased delta power (T = 2.37, PFDR = .03), decreased alpha power (T = -3.55, PFDR = .002) and increased gamma power (T = 3.14, PFDR = .008), reduced PAF (T = -2.60, P = .03), and longer mean duration of microstate C (T = 2.17, P = .03). CONCLUSIONS: Routine clinical EEG revealed quantitative neurophysiological differences between patients with and without catatonia in a transdiagnostic population with psychotic and mood disorders. PSD, alpha peak frequency, and microstate anomalies in catatonia shed light on its underlying pathophysiology, suggesting a probable neurodevelopmentally-related excitation/inhibition dysregulation. Importantly, this indicates that routine clinical EEG could be used for diagnostic biomarker development, which would ultimately improve early detection and treatment.