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广泛性焦虑症中注意力网络活动减弱及突显-默认模式转换增强:来自静息态脑电图微状态分析的证据

Diminished attention network activity and heightened salience-default mode transitions in generalized anxiety disorder: Evidence from resting-state EEG microstate analysis.

作者信息

Hao Xinyu, Ma Mohan, Meng Fanyu, Liang Hui, Liang Chunyu, Liu Xiaoya, Zhang Bo, Ju Yumeng, Liu Shuang, Ming Dong

机构信息

Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China; Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, People's Republic of China.

Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, People's Republic of China.

出版信息

J Affect Disord. 2025 Mar 15;373:227-236. doi: 10.1016/j.jad.2024.12.095. Epub 2024 Dec 30.

Abstract

Generalized anxiety disorder (GAD) is a common anxiety disorder characterized by excessive, uncontrollable worry and physical symptoms such as difficulty concentrating and sleep disturbances. Although functional magnetic resonance imaging (fMRI) studies have reported aberrant network-level activity related to cognition and emotion in GAD, its low temporal resolution restricts its ability to capture the rapid neural activity in mental processes. EEG microstate analysis offers millisecond-resolution for tracking the dynamic changes in brain electrical activity, thereby illuminating the neurophysiological mechanisms underlying the cognitive and emotional dysfunctions in GAD. This study collected 64-channel resting-state EEG data from 28 GAD patients and 28 healthy controls (HC), identifying five microstate classes (A-E) in both groups. Results showed that GAD patients exhibited significantly lower duration (p < 0.01), occurrence (p < 0.05), and coverage (p < 0.01) of microstate class D, potentially reflecting deficits in attention-related networks. Such alterations may contribute to the impairments in attention maintenance and cognitive control. Additionally, GAD patients displayed reduced transition probabilities in A → D, B → D, C → D, and E → D (all corrected p < 0.05), but increased in C → E (corrected p < 0.05) and E → C (corrected p < 0.01). These results highlight a significant reduction in the brain's ability to transition into microstate class D, alongside overactivity in switching between the default mode network and the salience network. Such neurophysiological changes may underlie cognitive control deficits, increased spontaneous rumination, and emotional regulation challenges observed in GAD. Together, these insights provide a new perspective for understanding the neurophysiological and pathological mechanisms underlying GAD.

摘要

广泛性焦虑障碍(GAD)是一种常见的焦虑症,其特征是过度、无法控制的担忧以及注意力难以集中和睡眠障碍等身体症状。尽管功能磁共振成像(fMRI)研究报告了广泛性焦虑障碍中与认知和情绪相关的异常网络水平活动,但其低时间分辨率限制了其捕捉心理过程中快速神经活动的能力。脑电图微状态分析提供毫秒级分辨率,用于跟踪脑电活动的动态变化,从而阐明广泛性焦虑障碍中认知和情绪功能障碍的神经生理机制。本研究收集了28名广泛性焦虑障碍患者和28名健康对照者(HC)的64通道静息态脑电图数据,在两组中识别出五个微状态类别(A - E)。结果显示,广泛性焦虑障碍患者的微状态D类的持续时间(p < 0.01)、出现频率(p < 0.05)和覆盖率(p < 0.01)显著降低,这可能反映了与注意力相关网络的缺陷。这种改变可能导致注意力维持和认知控制的受损。此外,广泛性焦虑障碍患者在A→D、B→D、C→D和E→D的转换概率降低(所有校正p < 0.05),但在C→E(校正p < 0.05)和E→C(校正p < 0.01)中增加。这些结果突出表明,大脑转换到微状态D类的能力显著降低,同时默认模式网络和突显网络之间的切换过度活跃。这种神经生理变化可能是广泛性焦虑障碍中观察到的认知控制缺陷、自发反刍增加和情绪调节挑战的基础。总之,这些见解为理解广泛性焦虑障碍的神经生理和病理机制提供了新的视角。

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