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EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

机译:EEG Microstates作为研究全脑神经元网络的时间动态的工具:综述

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The present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of large-scale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales. The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.
机译:本综述讨论了使用多通道脑电图(EEG)表征人脑的休息状态活性的良好方法。该方法涉及在大脑中检查电动微生物,其被定义为连续的短时间段,在此期间,头皮潜在字段的配置仍然是半稳态的,表明大规模网络节点之间的活动的准同时性。在参与者中可以可靠地识别出几种原型序列发生在重复序列中的少量原型微溶液。研究人员提出,这些MicroStates代表了自发意识精神过程链的基本构建块,其发生和时间动态决定了助化的质量。几项研究进一步证明了与神经和精神病病症相关的精神过程的干扰随着特定MICROUSTASE的时间动态的变化而表现为。组合EEG-FMRI研究和EEG源成像研究表明,由于使用FMRI鉴定的静态网络与休息状态网络密切相关。 EEG Microstates的时间序列的无垢特性解释了为什么可以在这种不同的时间尺度上观察到类似的网络。本综述将提供这些EEG Microstates的概述,可用于分析的方法,对这些微稳定的结果的功能解释及其行为和临床相关性。

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