Spatial characteristics of closed-loop TMS-EEG with occipital alpha-phase synchronized. (May 2023)

• Record Type: Journal Article
• Authors: Ding, Zhaohuan; Guan, Longzhou; He, Wenbo; Gu, Heng; Wang, Yong; Li, Xiaoli
• Is Part Of: Biomedical signal processing and control. Volume 83(2023)
• Publication Date: 2023-05
• Subjects: Closed-loop TMS-EEG -- PLI -- Brain Network -- Spatial Complexity; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2023.104650
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: We discussed the spatial characteristics (PLI, Brain Network and PCI) of closed-loop TMS-EEG data with occipital alpha-phase synchronization. We investigated the dependence of TMS-EEG connectivity on occipital lobe alpha phase. We hope that our research will be instructive for the future work of closed-loop TMS. Abstract: Objective: In a previous study, we designed a closed-loop TMS-EEG system synchronized with occipital alpha-phase, verified its phase prediction accuracy and discussed the reactivity indicators of the closed-loop system. However, the research on connectivity indicators of closed-loop TMS-EEG was remained lacking. In this study, the purpose of our research is to discuss the spatial characteristics of closed-loop TMS-EEG data with occipital alpha-phase synchronization. Method: We collected 30 healthy college students' closed-loop TMS-EEG data (15 men and 15 women, age 25.23 ± 2.74 years old) with 3–4 s as the stimulation interval, 100 % of the resting motor threshold (RMT) as the stimulation strength, and the left primary motor cortex (M1) as the target area, and calculated each frequency-band connectivity and brain network difference of these data under different alpha phase conditions (rising edge, falling edge, peak and trough). In addition, we also calculated the spatial complexity characterized by the perturbational complexity index (PCI) of the closed-loop TMS-EEG data. Results: The occipital lobe alpha phase EEG had a significant modulation effect on the gamma network, with the connectivity of the many channels under the phase180 condition being stronger than that under the phase 0 condition. Similarly, under the condition of phase 0, the gamma network had the lowest clustering coefficient (F = 7.592, df = 2.079, p = 0.001), the longest shortest path length (F = 7.638, df = 2.163, p = 0.001), and the largest small world attribute (F = 6.195, df = 2.422, p = 0.020), while the results were opposite under the phase180 condition. There were no significant differences in PCI values (F = 2.231, df = 2.538, p = 0.103) among the four phase conditions, but there was a smaller coefficient of intertrial PCI variation when stimulated at the phase90 condition (F = 3.275, df = 2.793, p = 0.029). Conclusion: We have comprehensively discussed the spatial characteristics of closed-loop TMS-EEG with occipital alpha-phase synchronization and hope that our research will be instructive for future work on closed-loop TMS.