Introduction: Repetitive transcranial magnetic stimulation (rTMS)is a noninvasive method, and its application in the treatment of primary insomnia (PI)is poorly researched. PI is considered to be a functional disorder with abnormal brain network connections. TMS combined electroencephalography (EEG)is a valuable method for directly probing excitability and dynamic connectivity of different regions in the brain. We aimed to investigate the therapeutic efficacy of rTMS and its impact on brain network connections in PI patients. Methods: Twenty patients with PI were recruited in this study and received 1 Hz rTMS treatment for 14 consecutive days. The severity of symptoms was evaluated using the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI)and the Epworth Sleepiness Scale (ESS). Twenty minutes TMS-EEG were performed before and immediately after treatment. EEG data was collected by 10-20 EEG system with the sample rate of 1024 Hz. Time-varying EEG network was analyzed using the adaptive directed transfer function. The EEG network results of patients were compared with those of 20 healthy subjects. Results: In the present study, we found that PSQI, ISI, and ESS ratings of the patients decreased significantly (P＜0.05)after rTMS treatment, and the improvement in ratings lasted one month. Compared with healthy subjects, single-pulse TMS targeting right posterior parietal cortex of PI patients before therapy showed excessive information outflow from the left occipital region, the frontal mid-line region and the right posterior temporal region, in succession. Meanwhile, inadequate information outflow was seen in the right central region, right parietal region, as well as in the right temporal region. Compared with prior treatment, PI patients showed increased information outflow in the left temporal region and decreased information outflow in the frontal mid-line region. Conclusion: Low frequency rTMS targeting the right posterior parietal cortex has significant positive effects on the treatment of PI that can last for at least one month and can reverse abnormal changes of time-varying EEG networks. © 2019 Elsevier B.V.