Several studies have shown that coordination among neural ensembles is a key to understand human cognition. A well charted path is to identify coordination states associated with cognitive functions from spectral changes in the oscillations of EEG or MEG. A growing number of studies suggest that the tendency to switch between coordination states, sculpts the dynamic repertoire of the brain and can be indexed by a measure known as metastability. In this article, we characterize perturbations in the metastability of global brain network dynamics following Transcranial Magnetic Stimulation that could quantify the duration for which information processing is altered. Thus allowing researchers to understand the network effects of brain stimulation, standardize stimulation protocols and design experimental tasks. We demonstrate the effect empirically using publicly available datasets and use a digital twin (a whole brain connectome model) to understand the dynamic principles that generate such observations. We observed a significant reduction in metastability, concurrent with an increase in coherence following single-pulse TMS reflecting the existence of a window where neural coordination is altered. The reduction in complexity was validated by an additional measure based on the Lempel-Ziv complexity of microstate labeled EEG data. Interestingly, higher frequencies in the EEG signal showed faster recovery in metastability than lower frequencies. The digital twin shed light on how the phase resetting introduced by the single-pulse TMS in local cortical networks can propagate globally, giving rise to changes in metastability and coherence.

中文翻译：

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亚稳定性指标反映大脑刺激后大脑动态工作点的整体变化

多项研究表明，神经元之间的协调是理解人类认知的关键。一条精心设计的路径是从脑电图或脑磁图振荡的频谱变化中识别与认知功能相关的协调状态。越来越多的研究表明，协调状态之间切换的倾向塑造了大脑的动态能力，并且可以通过一种称为亚稳定性的指标来索引。在本文中，我们描述了经颅磁刺激后全球大脑网络动力学亚稳定性的扰动，这可以量化信息处理改变的持续时间。从而使研究人员能够了解大脑刺激的网络效应，标准化刺激方案并设计实验任务。我们使用公开的数据集凭经验证明了这种效果，并使用数字孪生（全脑连接组模型）来理解生成此类观察结果的动态原理。我们观察到亚稳定性显着降低，同时单脉冲 TMS 后一致性增加，这反映了神经协调改变窗口的存在。复杂性的降低通过基于微状态标记脑电图数据的 Lempel-Ziv 复杂性的附加测量得到验证。有趣的是，脑电图信号中较高的频率比较低的频率显示亚稳定性的恢复更快。数字孪生揭示了局部皮质网络中单脉冲 TMS 引入的相位重置如何在全球范围内传播，从而引起亚稳定性和相干性的变化。