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静息态功能磁共振成像中的超慢脑电波动与静息态网络动力学相关。

Infra-slow EEG fluctuations are correlated with resting-state network dynamics in fMRI.

机构信息

Departments of Diagnostic Radiology, and Clinical Neurophysiology, Oulu University Hospital, 90029 OYS, Oulu, Finland, and Neuroscience Center, University of Helsinki, FI-00014 Helsinki, Finland.

出版信息

J Neurosci. 2014 Jan 8;34(2):356-62. doi: 10.1523/JNEUROSCI.0276-13.2014.

Abstract

Ongoing neuronal activity in the CNS waxes and wanes continuously across widespread spatial and temporal scales. In the human brain, these spontaneous fluctuations are salient in blood oxygenation level-dependent (BOLD) signals and correlated within specific brain systems or "intrinsic-connectivity networks." In electrophysiological recordings, both the amplitude dynamics of fast (1-100 Hz) oscillations and the scalp potentials per se exhibit fluctuations in the same infra-slow (0.01-0.1 Hz) frequency range where the BOLD fluctuations are conspicuous. While several lines of evidence show that the BOLD fluctuations are correlated with fast-amplitude dynamics, it has remained unclear whether the infra-slow scalp potential fluctuations in full-band electroencephalography (fbEEG) are related to the resting-state BOLD signals. We used concurrent fbEEG and functional magnetic resonance imaging (fMRI) recordings to address the relationship of infra-slow fluctuations (ISFs) in scalp potentials and BOLD signals. We show here that independent components of fbEEG recordings are selectively correlated with subsets of cortical BOLD signals in specific task-positive and task-negative, fMRI-defined resting-state networks. This brain system-specific association indicates that infra-slow scalp potentials are directly associated with the endogenous fluctuations in neuronal activity levels. fbEEG thus yields a noninvasive, high-temporal resolution window into the dynamics of intrinsic connectivity networks. These results support the view that the slow potentials reflect changes in cortical excitability and shed light on neuronal substrates underlying both electrophysiological and behavioral ISFs.

摘要

中枢神经系统(CNS)中的神经元活动持续不断地在广泛的时空尺度上波动。在人类大脑中,这些自发波动在血氧水平依赖(BOLD)信号中很明显,并在特定的大脑系统或“内在连接网络”内相关。在电生理记录中,快速(1-100 Hz)振荡的幅度动态和头皮电位本身都表现出在相同的亚慢(0.01-0.1 Hz)频率范围内的波动,其中 BOLD 波动很明显。虽然有几条证据表明 BOLD 波动与快速幅度动态相关,但仍不清楚全带宽脑电图(fbEEG)中的亚慢头皮电位波动是否与静息状态 BOLD 信号有关。我们使用同时进行的 fbEEG 和功能磁共振成像(fMRI)记录来解决头皮电位和 BOLD 信号中亚慢波动(ISFs)的关系。我们在这里表明,fbEEG 记录的独立成分与特定任务正性和任务负性 fMRI 定义的静息状态网络中皮质 BOLD 信号的子集选择性相关。这种特定于脑系统的关联表明,亚慢头皮电位与神经元活动水平的内源性波动直接相关。因此,fbEEG 为内在连接网络的动力学提供了一个非侵入性、高时间分辨率的窗口。这些结果支持缓慢电位反映皮质兴奋性变化的观点,并揭示了电生理和行为 ISFs 背后的神经元底物。

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