BOLD correlates of EEG topography reveal rapid resting-state network dynamics

脑电图 静息状态功能磁共振成像 默认模式网络 同步脑电与功能磁共振 地方政府 神经科学 心理学 神经生理学 模式识别(心理学) 人工智能 功能连接 计算机科学 认知心理学
作者
Juliane Britz,Dimitri Van De Ville,Christoph M. Michel
出处
期刊:NeuroImage [Elsevier BV]
卷期号:52 (4): 1162-1170 被引量:1027
标识
DOI:10.1016/j.neuroimage.2010.02.052
摘要

Resting-state functional connectivity studies with fMRI showed that the brain is intrinsically organized into large-scale functional networks for which the hemodynamic signature is stable for about 10 s. Spatial analyses of the topography of the spontaneous EEG also show discrete epochs of stable global brain states (so-called microstates), but they remain quasi-stationary for only about 100 ms. In order to test the relationship between the rapidly fluctuating EEG-defined microstates and the slowly oscillating fMRI-defined resting states, we recorded 64-channel EEG in the scanner while subjects were at rest with their eyes closed. Conventional EEG-microstate analysis determined the typical four EEG topographies that dominated across all subjects. The convolution of the time course of these maps with the hemodynamic response function allowed to fit a linear model to the fMRI BOLD responses and revealed four distinct distributed networks. These networks were spatially correlated with four of the resting-state networks (RSNs) that were found by the conventional fMRI group-level independent component analysis (ICA). These RSNs have previously been attributed to phonological processing, visual imagery, attention reorientation, and subjective interoceptive–autonomic processing. We found no EEG-correlate of the default mode network. Thus, the four typical microstates of the spontaneous EEG seem to represent the neurophysiological correlate of four of the RSNs and show that they are fluctuating much more rapidly than fMRI alone suggests.
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