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噪声提高了局部刺激的影响与大脑网络结构程度之间的关联。

Noise improves the association between effects of local stimulation and structural degree of brain networks.

机构信息

School of Mathematical Sciences, Beihang University, Beijing, China.

Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, China.

出版信息

PLoS Comput Biol. 2023 May 11;19(5):e1010866. doi: 10.1371/journal.pcbi.1010866. eCollection 2023 May.

Abstract

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes.

摘要

刺激局部区域会显著影响大脑活动模式,这可以用来研究认知功能的神经基础并改变病理性大脑状态。探索局部刺激的基本作用机制引起了越来越多的兴趣。然而,噪声幅度(神经动力学的一个重要元素)如何影响刺激诱导的大脑状态尚不清楚。在这里,我们使用大规模的生物物理模型,在不同的噪声幅度和刺激部位组合下,系统地研究了局部刺激的效果。我们证明,噪声幅度从区域和网络的角度,非线性和非均匀地调节刺激效果。此外,通过整合解剖网络的作用,我们表明,在不同的噪声幅度下,平均跨越所有刺激部位的未受刺激区域的峰值频率与结构连接高度正相关。至关重要的是,整体功能连接变化以及结构连接施加的约束随刺激部位的结构程度的改变与噪声幅度的关系是非单调的,在特定的噪声幅度范围内,这种关系会增强。此外,认知系统的局部刺激的影响取决于噪声幅度和平均结构程度之间的复杂相互作用。总的来说,这项工作为我们提供了理论上的认识,即噪声幅度和网络结构如何共同调节刺激过程中的大脑动力学,并为更好地预测和控制刺激结果提供了可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c13a/10205011/18107309162e/pcbi.1010866.g001.jpg

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