Alpha Frequency Dysrhythmia in Treatment-Resistant Schizophrenia: Associations with EEG Background Changes,...

Background: Treatment-resistant schizophrenia (TRS) affects approximately 20-30% of patients and is associated with significant disability. EEG abnormalities, particularly background slowing and disorganized alpha activity, have been reported in TRS, but the role of alpha rhythm instability-here termed alpha dysrhythmia-remains poorly understood. Objective: To compare the individual alpha frequency (IAF) between patients with TRS and those in clinical remission, to examine associations between alpha dysrhythmia and specific symptom domains (especially disorganization), and to investigate its relationship with EEG background changes. Methods: Eighty-nine patients with schizophrenia were included. Alpha dysrhythmia was defined as intraindividual variability of dominant alpha frequency exceeding 1 Hz across consecutive EEG epochs. Quantitative spectral analysis was performed using FFT on artifact-free 4-9 s epochs. Clinical assessment included PANSS (positive, negative, and disorganized subscales), the Dissociation scale, BPRS, Hamilton D/A, and the OCD scale. Group comparisons used the Mann-Whitney U test; correlations used Pearson and Spearman coefficients; and stepwise regression identified independent predictors. Results: Alpha dysrhythmia was present in 46.1% of patients. Significant negative correlations were found between dysrhythmia and therapeutic response. Significant positive correlations were found with PANSS disorganized symptoms and the Dissociation scale. The Mann-Whitney U test showed that the dysrhythmia group had higher mean ranks for EEG background factor (EEG BA), the Dissociation scale, and PANSS disorganized symptoms. Stepwise regression identified EEG BA and the Dissociation scale as independent predictors. Conclusions: Alpha dysrhythmia is frequent in TRS patients and is specifically associated with poorer therapeutic response, disorganized symptoms, and dissociation. EEG BA (reflecting background changes) may serve as a neurophysiological biomarker for identifying patients at risk for treatment resistance.