Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
Brain Topogr. 2013 Jan;26(1):98-109. doi: 10.1007/s10548-012-0235-0. Epub 2012 Jun 30.
With combined EEG-fMRI a powerful combination of methods was developed in the last decade that seems promising for answering fundamental neuroscientific questions by measuring functional processes of the human brain simultaneously with two complementary modalities. Recently, resting state networks (RSNs), representing brain regions of coherent BOLD fluctuations, raised major interest in the neuroscience community. Since RSNs are reliably found across subjects and reflect task related networks, changes in their characteristics might give insight to neuronal changes or damage, promising a broad range of scientific and clinical applications. The question of how RSNs are linked to electrophysiological signal characteristics becomes relevant in this context. In this combined EEG-fMRI study we investigated the relationship of RSNs and their correlated electrophysiological signals [electrophysiological correlation patterns (ECPs)] using a long (34 min) resting state scan per subject. This allowed us to study ECPs on group as well as on single subject level, and to examine the temporal stability of ECPs within each subject. We found that the correlation patterns obtained on group level show a large inter-subject variability. During the long scan the ECPs within a subject show temporal fluctuations, which we interpret as a result of the complex temporal dynamic of the RSNs.
在过去的十年中,结合 EEG-fMRI 开发了一种强大的方法组合,通过同时使用两种互补的模式来测量人类大脑的功能过程,似乎有望回答基础神经科学问题。最近,静息态网络(RSN)作为代表大脑区域内相干 BOLD 波动的区域,引起了神经科学界的极大兴趣。由于 RSN 在不同被试之间是可靠存在的,并反映了与任务相关的网络,因此它们特征的变化可能会提供有关神经元变化或损伤的信息,有望带来广泛的科学和临床应用。在这种情况下,RSN 与电生理信号特征的联系问题变得很重要。在这项结合 EEG-fMRI 的研究中,我们使用每个被试长(34 分钟)的静息状态扫描来研究 RSN 及其相关的电生理信号(电生理相关模式)之间的关系。这使我们能够在组和个体水平上研究 ECP,并检查每个被试内 ECP 的时间稳定性。我们发现,在组水平上获得的相关模式表现出很大的个体间变异性。在长时间的扫描中,一个被试内的 ECP 会出现时间波动,我们将其解释为 RSN 复杂的时间动态的结果。