Predicting the long-term after-effects of rTMS in autism spectrum disorder using temporal variability analysis of scalp EEG

Abstract Objective. Repetitive transcranial magnetic stimulation (rTMS) emerges as a useful therapy for autism spectrum disorder (ASD) clinically. Whereas the mechanisms of action of rTMS on ASD are not fully understood, and no biomarkers until now are available to reliably predict the follow-up rTMS efficacy in clinical practice. Approach. In the current work, the temporal variability was investigated in resting-state electroencephalogram of ASD patients, and the nonlinear complexity of related time-varying networks was accordingly evaluated by fuzzy entropy. Main results. The results showed the hyper-variability in the resting-state networks of ASD patients, while three week rTMS treatment alleviates the hyper fluctuations occurring in the frontal-parietal and frontal-occipital connectivity and further contributes to the ameliorative ASD symptoms. In addition, the changes in variability network properties are closely correlated with clinical scores, which further serve as potential predictors to reliably track the long-term rTMS efficacy for ASD. Significance. The findings consistently demonstrated that the temporal variability of time-varying networks of ASD patients could be modulated by rTMS, and related variability properties also help predict follow-up rTMS efficacy, which provides the potential for formulating individualized treatment strategies for ASD (ChiCTR2000033586).