期刊
JOURNAL OF NEUROSCIENCE
卷 34, 期 2, 页码 356-362出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.0276-13.2014
关键词
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资金
- Academy of Finland [111711, 123772, 253130, 256472]
- Strategic Centre for Science, Technology and Innovation SalWe Grant [WP 302]
- Finnish Medical Foundation
- Academy of Finland (AKA) [256472, 256472] Funding Source: Academy of Finland (AKA)
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.
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