• J. Neurosci. · Jan 2014

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

    • Tuija Hiltunen, Jussi Kantola, Ahmed Abou Elseoud, Pasi Lepola, Kalervo Suominen, Tuomo Starck, Juha Nikkinen, Jukka Remes, Osmo Tervonen, Satu Palva, Vesa Kiviniemi, and J Matias Palva.
    • Departments of Diagnostic Radiology, and Clinical Neurophysiology, Oulu University Hospital, 90029 OYS, Oulu, Finland, and Neuroscience Center, University of Helsinki, FI-00014 Helsinki, Finland.
    • J. Neurosci. 2014 Jan 8;34(2):356-62.

    AbstractOngoing 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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