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

Britz, Juliane; Van De Ville, Dimitri; Michel, Christoph M.

doi:10.1016/j.neuroimage.2010.02.052

Cited by 1,070Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsNeural dynamics and brain function

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

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Britz, Juliane, Van De Ville, Dimitri, Michel, Christoph M.·2010·NeuroImage

DOI 10.1016/j.neuroimage.2010.02.052

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Abstract

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 10s. 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.

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EEG microstates correlate with resting-state fMRI signal.
“The EEG microstates have been found to correlate with the fMRI signal in the resting state (173–175).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [174]

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Cognitive manipulation of brain electric microstates
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EEG microstates of wakefulness and NREM sleep
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Dynamic BOLD functional connectivity in humans and its electrophysiological correlates
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Resting-State Quantitative Electroencephalography Reveals Increased Neurophysiologic Connectivity in Depression
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Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia
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EEG Recorded from the Ear: Characterizing the Ear-EEG Method
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Graph Frequency Analysis of Brain Signals
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Analysis of Multimodal Neuroimaging Data
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The EEG microstate topography is predominantly determined by intracortical sources in the alpha band
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The brain matures with stronger functional connectivity and decreased randomness of its network
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Within and between-person correlates of the temporal dynamics of resting EEG microstates
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EEG Resting-State Large-Scale Brain Network Dynamics Are Related to Depressive Symptoms
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EEG microstate features for schizophrenia classification
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Effects of morphine and alcohol on functional brain connectivity during “resting state”: a placebo-controlled crossover study in healthy young men
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P4‐158: Nonstationarity in the ‘resting brain's’ modular architecture
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Comparison of QEEG Findings between Adolescents with Attention Deficit Hyperactivity Disorder (ADHD) without Comorbidity and ADHD Comorbid with Internet Gaming Disorder
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Neurophysiological Studies of Auditory Verbal Hallucinations
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Authors: Britz, J., Van De Ville, D., & Michel, C. M.
Affiliations: University of Geneva (CH)
Corresponding author: Britz, Juliane
ORCID: Britz, Juliane
Michel, Christoph M.
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2010-10
Volume: 52
Issue: 4
Pages: 1162-1170
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2010.02.052
OpenAlex: W2131216884
Cited by: 1,070
References: 72
Citations by year: 2026: 139 · 2025: 161 · 2024: 101 · 2023: 97 · 2022: 89 · 2021: 76 · 2020: 77 · 2019: 43 · 2018: 45 · 2017: 45 · 2016: 33 · 2015: 22 · 2014: 36 · 2013: 40 · 2012: 39
FWCI: 20.56
Type: journal article
Language: en
Open access: green
infoscience.epfl.ch
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
Archive ouverte UNIGE (University of Geneva) (submittedVersion)
Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
Funders: Swiss National Science Foundation (32003B-118315, PP00P2-123438)
Center for Biomedical Imaging (CIBM) of the Geneva and Lausanne Universities
Leenaards and Louis-Jeantet Foundations
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords: resting-state networks, EEG microstates, BOLD signal, EEG-fMRI correlation, hemodynamic response function, spontaneous EEG, functional connectivity, default mode network, independent component analysis, large-scale brain networks, network dynamics
MeSH terms: Action Potentials, Adult, Biological Clocks, Brain, Electroencephalography, Female, Humans, Magnetic Resonance Imaging, Male, Nerve Net, Rest

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

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