Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment - Zhu, Lin; Dang, Ge; Wu, Wei; Zhou, Junhong; Shi, Xue; Su, Xiaolin; Ren, Huixia; Pei, Zian; Lan, Xiaoyong; Lian, Chongyuan; Xie, Peng; Guo, Yi (Frontiers in Neuroscience, 2023)
Background: Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited. Objective: This study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS. Methods: Thirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI). Results: After treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8–10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment. Conclusions: Based on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization.