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基于爆发性同步的脑调制可降低脑网络的超敏反应:一项计算模型研究

Explosive Synchronization-Based Brain Modulation Reduces Hypersensitivity in the Brain Network: A Computational Model Study.

作者信息

Kim MinKyung, Harris Richard E, DaSilva Alexandre F, Lee UnCheol

机构信息

Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States.

Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States.

出版信息

Front Comput Neurosci. 2022 Mar 3;16:815099. doi: 10.3389/fncom.2022.815099. eCollection 2022.

Abstract

Fibromyalgia (FM) is a chronic pain condition that is characterized by hypersensitivity to multimodal sensory stimuli, widespread pain, and fatigue. We have previously proposed explosive synchronization (ES), a phenomenon wherein a small perturbation to a network can lead to an abrupt state transition, as a potential mechanism of the hypersensitive FM brain. Therefore, we hypothesized that converting a brain network from ES to general synchronization (GS) may reduce the hypersensitivity of FM brain. To find an effective brain network modulation to convert ES into GS, we constructed a large-scale brain network model near criticality (i.e., an optimally balanced state between order and disorders), which reflects brain dynamics in conscious wakefulness, and adjusted two parameters: local structural connectivity and signal randomness of target brain regions. The network sensitivity to global stimuli was compared between the brain networks before and after the modulation. We found that only increasing the local connectivity of hubs (nodes with intense connections) changes ES to GS, reducing the sensitivity, whereas other types of modulation such as decreasing local connectivity, increasing and decreasing signal randomness are not effective. This study would help to develop a network mechanism-based brain modulation method to reduce the hypersensitivity in FM.

摘要

纤维肌痛(FM)是一种慢性疼痛病症,其特征为对多模式感觉刺激过敏、广泛疼痛和疲劳。我们之前提出了爆发性同步(ES),即网络的一个小扰动可导致突然的状态转变这一现象,作为FM大脑过敏的一种潜在机制。因此,我们假设将大脑网络从ES转换为一般同步(GS)可能会降低FM大脑的过敏反应。为了找到一种将ES转换为GS的有效大脑网络调制方法,我们构建了一个接近临界状态(即秩序与无序之间的最佳平衡状态)的大规模大脑网络模型,该模型反映清醒状态下的大脑动力学,并调整了两个参数:目标脑区的局部结构连通性和信号随机性。比较了调制前后大脑网络对全局刺激的敏感性。我们发现,只有增加枢纽(连接密集的节点)的局部连通性才能将ES转变为GS,降低敏感性,而其他类型的调制,如降低局部连通性、增加和降低信号随机性则无效。本研究将有助于开发一种基于网络机制的大脑调制方法,以降低FM中的过敏反应。

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