Abnormality of inter-network dynamic interaction in resting-state brains of schizophrenic patients

Resting-state functional connectivity (rs-FC) analyses have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and disconnectivity of intrinsic brain networks. However, these studies assumed temporal stationarity of rs-FCs, while the temporal dynamic of rs-FCs is rarely explored. Here, we test the variability of spontaneous fluctuation in rs-FCs of schizophrenic patients, using a measure of amplitude of low-frequency fluctuation (ALFF) of dynamic functional connectivity. Two-tailed two-sample t-tests and nonlinear support vector machines were employed to classify 24 schizophrenic patients from 25 healthy controls. The experimental results demonstrated that 81.3% of subjects were correctly classified by leave-one-out cross-validation. Moreover, the majority of the most discriminating functional connections were located across the identified networks, indicating that the inter-network dynamic interaction changes existed in schizophrenic patients. The current study may shed new light on the pathophysiological mechanism of schizophrenia and suggests that the abnormal temporal communication across networks may provide potential biomarkers for its clinical diagnosis.