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

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage Pub Date : 2025-06-07 DOI:10.1016/j.neuroimage.2025.121318

Hechun Li , Hongru Shi , Sisi Jiang , Changyue Hou , Haonan Pei , Hanxi Wu , María Luisa Bringas Vega , Gang Yao , Dezhong Yao , Cheng Luo

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引用次数: 0

Abstract

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.

Abstract Image

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拮抗网络靶向tDCS对大脑共激活模式的影响取决于网络的电场：一项同步tDCS- fmri研究

脑网络应该是非侵入性脑刺激的理想目标，因为网络功能障碍是各种神经精神疾病的共同特征。了解神经网络靶向刺激的机制对推进其临床应用至关重要。材料与方法本研究采用同步网络靶向经颅直流电刺激（tDCS）和功能磁共振成像（fMRI）来研究tDCS靶向拮抗网络对脑动力学的影响。共有143名健康参与者被招募并被分配接受中央执行网络（CEN）靶向tDCS （c -目标组），默认模式网络（DMN）靶向tDCS （d -目标组）或假手术tDCS（假手术组）。收集所有受试者的fMRI数据，分为刺激前、刺激中、刺激后三个部分。采用个体头部模型模拟个体电场强度。确定了六种反复出现的大脑模式（共激活模式，CAPs）。计算了这些cap的时间指标（发生时间、分数时间、持续时间）及其转移概率。本研究首先考察了c -靶向/ d -靶向/假tDCS对颞叶指数的影响，并进一步探讨了脑网络EF强度对颞叶指数改变的贡献。结果sc靶向tDCS显著增加了DMN主导的cap的时间指标和其他cap向DMN主导的cap过渡的概率。同时，在c靶tDCS过程中，CEN主导的CAP时间指数下降，向这些CAP过渡的概率也有所下降。相比之下，d靶向tDCS对脑动力学只有轻微的影响，而假tDCS没有明显的影响。进一步的融合分析显示，在刺激期间，显著性网络中的EF强度对cap的时间指数有很大的贡献，这突出了三重网络之间的紧密相互作用。此外，将大贡献网络的EF强度与刺激前时间指数相结合，可以有效预测刺激过程中cap的时间指数。这些发现表明，针对c的tDCS可以调节脑动力学，并强调了刺激过程中网络EF的关键作用。结论本研究证实了网络靶向tDCS调节脑动力学的有效性和可行性，为治疗以脑动力学异常为特征的神经精神疾病提供了新的选择。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

NeuroImage 医学-核医学

CiteScore

11.30

自引率

10.50%

发文量

809

审稿时长

63 days

期刊介绍： NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.