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

被引:724
作者
Britz, Juliane [1 ,2 ]
Van De Ville, Dimitri [3 ,4 ]
Michel, Christoph M. [1 ,2 ,5 ]
机构
[1] Univ Geneva, Dept Fundamental Neurosci, CH-1211 Geneva 4, Switzerland
[2] Univ Geneva, EEG Brain Mapping Core, Biomed Imaging Ctr CIBM, CH-1211 Geneva 4, Switzerland
[3] Univ Geneva, Dept Radiol & Med Informat, CH-1211 Geneva 4, Switzerland
[4] Ecole Polytech Fed Lausanne, Inst Bioengn, CH-1015 Lausanne, Switzerland
[5] Univ Geneva, Sch Med, Dept Neurol, CH-1211 Geneva 4, Switzerland
基金
瑞士国家科学基金会;
关键词
EEG; fMRI; EEG microstates; EEG topography; Resting state; ICA; GLM; Rapid dynamics; Resting-state networks; Default-mode network; BRAIN ACTIVITY; DEFAULT-MODE; FUNCTIONAL CONNECTIVITY; NEURONAL OSCILLATIONS; ACTIVITY FLUCTUATIONS; FMRI DATA; SEGMENTATION; CORTEX; IDENTIFICATION; CONSCIOUSNESS;
D O I
10.1016/j.neuroimage.2010.02.052
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
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. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:1162 / 1170
页数:9
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