Effects of antagonistic network-targeted tDCS on brain co-activation patterns depends on the networks’ electric field: a simultaneous tDCS-fMRI study

Background: Brain networks should be ideal targets for non-invasive brain stimulation, as network dysfunction is a common feature of various neuropsychiatric disorders. Understanding the mechanisms of network-targeted stimulation is essential for advancing its clinical applications. Material and met...

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Main Authors: Hechun Li, Hongru Shi, Sisi Jiang, Changyue Hou, Haonan Pei, Hanxi Wu, María Luisa Bringas Vega, Gang Yao, Dezhong Yao, Cheng Luo
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:NeuroImage
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Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925003210
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Summary:Background: Brain networks should be ideal targets for non-invasive brain stimulation, as network dysfunction is a common feature of various neuropsychiatric disorders. Understanding the mechanisms of network-targeted stimulation is essential for advancing its clinical applications. Material and method: The current study utilized simultaneous network-targeted transcranial direct current stimulation(tDCS) and functional magnetic resonance imaging (fMRI) to investigate the effects of tDCS targeting antagonistic networks on brain dynamics. A total of 143 healthy participants were recruited and assigned to receive central executive network (CEN)-targeted tDCS (C-targeted group), default mode network (DMN)-targeted tDCS (D-targeted group), or sham tDCS (sham group). fMRI data with three sections (pre-stimulation, during-stimulation, post-stimulation) were collected across all subjects. Individual electric field (EF) strength was simulated using individual head model. Six recurring brain patterns (co-activation patterns, CAPs) were identified. The temporal indices of these CAPs (occurrence, fraction time, persistence time) and their transition probabilities were calculated. This study first examined the effects of C-targeted / D-targeted / sham tDCS on temporal indices and further explored the contribution of brain networks’ EF strength on the altered temporal indices. Results: C-targeted tDCS significantly increased the temporal indices of CAPs dominated by DMN and the transition probabilities from other CAPs to DMN-dominated CAPs during stimulation. Meanwhile, the decreased temporal indices of CAP dominated by CEN, and its transition probabilities to these CAPs were also found during C-targeted tDCS. In contrast, the d-targeted tDCS had only a slight effect on brain dynamics, while sham tDCS showed no significant impact. Further fusion analyses revealed that the EF strength in the salience network made a large contribution to the temporal indices of CAPs during stimulation, highlighting tight interactions within the triple networks. Moreover, integrating the EF strength of networks with large contributions and the pre-stimulation temporal indices effectively predicted the temporal indices of CAPs during stimulation. These findings suggest that C-targeted tDCS can modulate brain dynamics and emphasize the critical role of networks’ EF during stimulation. Conclusion: This study demonstrates the effectiveness and feasibility of network-targeted tDCS in modulating brain dynamics, providing a new choice for treating neuropsychiatric disorders characterized by aberrant brain dynamics.
ISSN:1095-9572