Erratum: Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

[This corrects the article DOI: 10.1038/s41537-017-0023-7.].

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome.

Diffusion tensor imaging study of the anterior limb of internal capsules in neuroleptic-naive schizophrenia.

RATIONALE AND OBJECTIVES: Abnormalities in brain structure have been implicated in psychosis. Herein, we investigated the differences in fractional anisotropy (FA) and average diffusion coefficient (ADC) in the bilateral anterior limb of internal capsules between neuroleptic-naive schizophrenic patients and appropriately matched healthy controls. MATERIALS AND METHODS: Magnetic resonance imaging was performed with a 1.5 T superconductive MR scanner, and diffusion tensor imaging was carried out in 21 neuroleptic-naive schizophrenic patients and 18 matched healthy controls. FA and ADC were measured by region of interest analysis. RESULTS: Compared with healthy controls, the neuroleptic-naive schizophrenic patients showed significantly reduced FA in the bilateral anterior limb of the internal capsule. However, the difference in the ADC values between the patients and the controls was not significant. CONCLUSIONS: FA of the bilateral anterior limb of the internal capsule was reduced in neuroleptic-naive schizophrenic patients, indicating that the integrity of the white matter of the bilateral thalamus-frontal connection or the bilateral thalamus-anterior cingulate gyrus connection was destroyed.