Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging
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Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity.
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EEG correlates of resting-state networks have distinct spectral signatures that characterize how neural oscillations support inter-regional interactions within networks.
“The EEG correlates of resting state networks exhibit their distinct spectral signatures, characterizing the way by which neural oscillations support inter-regional interactions within networks (144, 159).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [144]
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Electrophysiological source imaging: A noninvasive window to brain dynamics
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- Authors
- Liu, Z., de Zwart, J. A., Chang, C., Duan, Q., van Gelderen, P., & Duyn, J. H.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Liu, Zhongming
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-06-24
- Volume
- 24
- Issue
- 11
- Pages
- 3080-3089
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC4200040
- OpenAlex
- W2051472919
- Cited by
- 22
- References
- 61
- Citations by year
- 2025: 3 · 2021: 6 · 2020: 2 · 2018: 2 · 2017: 2 · 2016: 1 · 2015: 4 · 2014: 2
- FWCI
- 1.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Cerebral Cortex (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- spontaneous brain activity, resting-state networks, subspace analysis, EEG spectral features, large-scale neural networks
- MeSH terms
- Adult, Brain, Brain Mapping, Electroencephalography, Evoked Potentials, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Oxygen, Photic Stimulation, Spectrum Analysis, Statistics as Topic, Visual Pathways, Young Adult
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