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Published on: November 19, 2014
High-density EEG study in patients with schizophrenia treated with cariprazine
Pál Czobor1, Brigitta Kakuszi1, Máté Fullajtár1
1Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.
Background:
Schizophrenia is marked by persistent negative and cognitive symptoms that remain difficult to treat. Cariprazine, a dopamine D3/D2 partial agonist, has demonstrated efficacy in these domains, making it essential to clarify its neurophysiological mechanisms both for future drug discovery and clinical application. Resting-state EEG spectral analysis provides a non-invasive and translational tool for monitoring neurophysiological changes related to treatment. However, data on EEG spectral effects in human patients treated with cariprazine are currently lacking.
Methods:
In this open-label investigation, 27 patients with schizophrenia underwent high-density resting-state EEG before and during cariprazine treatment. Power spectral analyses were conducted across frequency bands and cortical regions, with ROI analyses targeting gamma-activity in DLPFC, IFG, and TPJ. Symptom changes were measured using the Positive and Negative Syndrome Scale.
Results:
Cariprazine treatment led to symptom improvement, particularly in negative and general domains. EEG analyses showed increased spectral power, most prominently in the theta and alpha bands, mirroring findings from the only available in vivo preclinical study, which also reported theta and alpha elevations in rodents. Symptom reduction was specifically associated with increased theta and decreased delta power. Moreover, baseline gamma-activity-especially in the IFG and DLPFC-predicted treatment response, with Receiver Operating Characteristic analyses yielding AUC values of 0.72-0.92 and cross-validated classification accuracies exceeding 70%.
Conclusions:
Together, our results demonstrate that resting-state EEG spectral measures reflect neurophysiological correlates of cariprazine response. Furthermore, the findings reinforce the cross-species translatability of spectral measures and support EEG biomarkers as promising translational tools for predicting and monitoring treatment outcomes in schizophrenia.
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