Computer methods and programs in biomedicine · 2025
Nonlinear dose-response relationship in tDCS-induced brain network synchrony: A resting-state whole-brain model analysis.
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Shao Hongyuan, Gu Guanghua, Guo Xiaonan, Li Xiaoli, Cui Dong
Аннотация
BACKGROUND: Transcranial Direct Current Stimulation (tDCS) is a non-invasive neuroregulation technique that influences brain dynamics, widely used to enhance cognitive abilities, treat neurological disorders, and aid rehabilitation. With the advancement of computational neuroscience, dynamic modeling analysis has become an important tool for understanding the mechanisms of tDCS.
METHODS: In this study, we constructed a resting-state whole-brain model, similar to the human brain. By simulating tDCS, we analyzed its effects at different intensities on the whole-brain model. We used various electrophysiological measures to assess the impact of tDCS on brain functional networks and electrophysiological characteristics. In addition, we analyzed the network structures influenced by different tDCS intensities using graph theory measures and the small-world index. Finally, we analyzed the factors that could influence the observed phenomena.
RESULTS: The results indicate that within a certain range, tDCS can enhance the synchronicity of brain functional networks; however, excessive intensity results in a significant reduction in the benefits. We observed that electrical stimulation induces complex electrophysiological activities across widespread brain regions through network propagation. Networks influenced by low tDCS intensity achieve optimal states in graph theory metrics. Conversely, high tDCS intensity damages network structures, reducing information transmission efficiency. Finally, we found that these phenomena are closely related to the unique physiological structure of the human brain.
CONCLUSIONS: This study demonstrates a nonlinear dose-response relationship, revealing that network synchrony achieves optimal states only at appropriate tDCS intensities. This research provides theoretical support for the clinical application of tDCS and scientific guidance for selecting the most effective stimulation protocols.
METHODS: In this study, we constructed a resting-state whole-brain model, similar to the human brain. By simulating tDCS, we analyzed its effects at different intensities on the whole-brain model. We used various electrophysiological measures to assess the impact of tDCS on brain functional networks and electrophysiological characteristics. In addition, we analyzed the network structures influenced by different tDCS intensities using graph theory measures and the small-world index. Finally, we analyzed the factors that could influence the observed phenomena.
RESULTS: The results indicate that within a certain range, tDCS can enhance the synchronicity of brain functional networks; however, excessive intensity results in a significant reduction in the benefits. We observed that electrical stimulation induces complex electrophysiological activities across widespread brain regions through network propagation. Networks influenced by low tDCS intensity achieve optimal states in graph theory metrics. Conversely, high tDCS intensity damages network structures, reducing information transmission efficiency. Finally, we found that these phenomena are closely related to the unique physiological structure of the human brain.
CONCLUSIONS: This study demonstrates a nonlinear dose-response relationship, revealing that network synchrony achieves optimal states only at appropriate tDCS intensities. This research provides theoretical support for the clinical application of tDCS and scientific guidance for selecting the most effective stimulation protocols.