EEG as a Predictor of Transition from Clinical High Risk to Schizophrenia

AbstractBackgroundPrognostic markers capable of predicting future conversion to schizophrenia from a clinical high-risk state are vital for early intervention. Electroencephalography (EEG), a non-invasive measure of brain activity, has been widely studied in early psychosis research. While EEG biomarkers have shown promise for diagnosis, their predictive value for psychosis conversion remains unclear. This systematic review evaluates baseline EEG differences between clinical high risk (CHR) individuals who later develop psychosis and those who do not.MethodsA systematic review of articles on Pubmed, CINAHL and APA Psycarticles was conducted in October 2024, with additional studies being collected through hand search. Studies comparing EEG markers in CHR converters and non-converters were included. Narrative synthesis was used to observe the findings due to variance in the included methodologies.ResultsOut of 899 screened studies, 29 met inclusion criteria. Findings on EEG prognostic value were mixed, though Mismatch Negativity (MMN) and P300 event-related potentials (ERPs), as well as elevated theta and delta power in resting-state EEG, showed the highest consistency in predicting conversion. P50 sensory gating deficits did not emerge as a reliable predictor.DiscussionOur findings were contextualised in cross-sectional studies of clinical high risk and first episode psychosis. The relative sensitivity of biomarkers, in terms of prediction and use in the prodromal phase was discussed. The limitations of our collected literature, in terms of inconsistency between clinical and neurophysiological measures was noted. Future larger, standardised, multi-centre studies are needed to validate findings for the use of EEG in predicting future conversion to psychosis. We further propose that including task-related EEG indices that tap into transdiagnostic symptom dimensions could widen the range of promising biomarkers.Keywords: Psychosis, Schizophrenia, Transition, EEG markers, MMN, P300, Theta, Delta