Transcranial magnetic stimulation regulates brain functional network dynamics in stroke patients: a randomised controlled trial

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for stroke patients, but its underlying neural mechanisms remain largely unknown. This study aimed to investigate changes in brain functional connectome dynamics in stroke patients whose were treated with rTMS as well as to explore their relationship with treatment outcomes. Sixty-four stroke patients were randomly divided into rTMS (n = 34) or no-rTMS (n = 30) groups. Resting-state functional MRI data and clinical behavioral variables were collected before and after intervention. A multi-layer network model was used to quantify functional network switching rate, followed by performance of comparison and correlation analyses to examine group differences in the treatment-induced changes in the network dynamics as well as their relation to clinical improvement. Moreover, multivariate linear regression analyses were pursued to test whether the functional connectome dynamic changes could predict rTMS treatment outcome. Network switching rate changes in the rTMS group were greater than those in the no-rTMS group. Specifically, at the whole-brain level, the rTMS group had a higher network switching rate change than no-rTMS group (p = 0.014); at the sub-network level, the network switching rate changes of the sensorimotor, default-mode, and fronto-parietal networks in the rTMS group were higher than those of the no-rTMS group (p < 0.05); and at the nodal level, the rTMS group had higher network switching rate changes than the no-rTMS group in the prefrontal cortex, cingulate gyrus, and inferior parietal lobule (p < 0.05), but the network switching rate change of the precentral gyrus in the rTMS group was lower than that in the no-rTMS group (p = 0.038). Additionally, network switching rate change in the subparietal lobule was positively correlated with the improvement degree of motor function in the rTMS group (p = 0.016). Moreover, Multivariate linear regression analyses showed that baseline connectome dynamics could predict symptom improvement in the rTMS group to a certain extent. Our findings may improve the understanding of the neural mechanism of rTMS treatment for stroke from the perspective of network dynamics, and may have clinical implications for offering potential predictor for monitoring rTMS treatment efficacy in stroke patients to some extent. Trial registration This trial was registered at https://www.chictr.org.cn/ (ChiCTR1800019452).

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Publication Details

Journal
Journal of NeuroEngineering and Rehabilitation
Published
2025-11-10
DOI
https://doi.org/10.1186/s12984-025-01776-9
Primary Topic
Transcranial Magnetic Stimulation Studies
Type
article
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article

Transcranial magnetic stimulation regulates brain functional network dynamics in stroke patients: a randomised controlled trial

Xiaoying Zhuang, Shuting Qiu, Xiaoyang Wang, Yin Qin et al.
Journal of NeuroEngineering and Rehabilitation
Transcranial Magnetic Stimulation Studies
article

Transcranial magnetic stimulation regulates brain functional network dynamics in stroke patients: a randomised controlled trial

Xiaoying Zhuang, Shuting Qiu, Xiaoyang Wang, Yin Qin, Xiaoying Liu, Yuting Tang
article en

Abstract

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for stroke patients, but its underlying neural mechanisms remain largely unknown. This study aimed to investigate changes in brain functional connectome dynamics in stroke patients whose were treated with rTMS as well as to explore their relationship with treatment outcomes. Sixty-four stroke patients were randomly divided into rTMS (n = 34) or no-rTMS (n = 30) groups. Resting-state functional MRI data and clinical behavioral variables were collected before and after intervention. A multi-layer network model was used to quantify functional network switching rate, followed by performance of comparison and correlation analyses to examine group differences in the treatment-induced changes in the network dynamics as well as their relation to clinical improvement. Moreover, multivariate linear regression analyses were pursued to test whether the functional connectome dynamic changes could predict rTMS treatment outcome. Network switching rate changes in the rTMS group were greater than those in the no-rTMS group. Specifically, at the whole-brain level, the rTMS group had a higher network switching rate change than no-rTMS group (p = 0.014); at the sub-network level, the network switching rate changes of the sensorimotor, default-mode, and fronto-parietal networks in the rTMS group were higher than those of the no-rTMS group (p < 0.05); and at the nodal level, the rTMS group had higher network switching rate changes than the no-rTMS group in the prefrontal cortex, cingulate gyrus, and inferior parietal lobule (p < 0.05), but the network switching rate change of the precentral gyrus in the rTMS group was lower than that in the no-rTMS group (p = 0.038). Additionally, network switching rate change in the subparietal lobule was positively correlated with the improvement degree of motor function in the rTMS group (p = 0.016). Moreover, Multivariate linear regression analyses showed that baseline connectome dynamics could predict symptom improvement in the rTMS group to a certain extent. Our findings may improve the understanding of the neural mechanism of rTMS treatment for stroke from the perspective of network dynamics, and may have clinical implications for offering potential predictor for monitoring rTMS treatment efficacy in stroke patients to some extent. Trial registration This trial was registered at https://www.chictr.org.cn/ (ChiCTR1800019452).

Journal of NeuroEngineering and RehabilitationVol. 22(1)
Fujian Medical University (CN), The 180th Hospital of PLA (CN)
Openalex Percentile: Top 59%
Transcranial Magnetic Stimulation Studies
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