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动态功能网络连接状态的脑电图特征

EEG Signatures of Dynamic Functional Network Connectivity States.

作者信息

Allen E A, Damaraju E, Eichele T, Wu L, Calhoun V D

机构信息

The Mind Research Network & LBERI, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA.

Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA.

出版信息

Brain Topogr. 2018 Jan;31(1):101-116. doi: 10.1007/s10548-017-0546-2. Epub 2017 Feb 22.

Abstract

The human brain operates by dynamically modulating different neural populations to enable goal directed behavior. The synchrony or lack thereof between different brain regions is thought to correspond to observed functional connectivity dynamics in resting state brain imaging data. In a large sample of healthy human adult subjects and utilizing a sliding windowed correlation method on functional imaging data, earlier we demonstrated the presence of seven distinct functional connectivity states/patterns between different brain networks that reliably occur across time and subjects. Whether these connectivity states correspond to meaningful electrophysiological signatures was not clear. In this study, using a dataset with concurrent EEG and resting state functional imaging data acquired during eyes open and eyes closed states, we demonstrate the replicability of previous findings in an independent sample, and identify EEG spectral signatures associated with these functional network connectivity changes. Eyes open and eyes closed conditions show common and different connectivity patterns that are associated with distinct EEG spectral signatures. Certain connectivity states are more prevalent in the eyes open case and some occur only in eyes closed state. Both conditions exhibit a state of increased thalamocortical anticorrelation associated with reduced EEG spectral alpha power and increased delta and theta power possibly reflecting drowsiness. This state occurs more frequently in the eyes closed state. In summary, we find a link between dynamic connectivity in fMRI data and concurrently collected EEG data, including a large effect of vigilance on functional connectivity. As demonstrated with EEG and fMRI, the stationarity of connectivity cannot be assumed, even for relatively short periods.

摘要

人类大脑通过动态调节不同的神经群体来实现目标导向行为。不同脑区之间的同步性或缺乏同步性被认为与静息态脑成像数据中观察到的功能连接动力学相对应。在大量健康成年人类受试者样本中,我们利用功能成像数据上的滑动窗口相关方法,较早前证明了不同脑网络之间存在七种不同的功能连接状态/模式,这些状态/模式在时间和受试者之间可靠地出现。这些连接状态是否对应有意义的电生理特征尚不清楚。在本研究中,我们使用了一个包含在睁眼和闭眼状态下同时采集的脑电图(EEG)和静息态功能成像数据的数据集,证明了先前研究结果在独立样本中的可重复性,并识别出与这些功能网络连接变化相关的EEG频谱特征。睁眼和闭眼条件显示出与不同EEG频谱特征相关的共同和不同的连接模式。某些连接状态在睁眼情况下更为普遍,而有些仅出现在闭眼状态。两种条件都表现出丘脑皮质反相关性增加的状态,这与EEG频谱α功率降低以及δ和θ功率增加有关,可能反映了困倦。这种状态在闭眼状态下更频繁出现。总之,我们发现功能磁共振成像(fMRI)数据中的动态连接与同时采集的EEG数据之间存在联系,包括警觉性对功能连接的重大影响。正如EEG和fMRI所显示的,即使在相对较短的时间段内,也不能假设连接的平稳性。

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