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Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest
Open accessAbstract
We assessed the relation between hemodynamic and electrical indices of brain function by performing simultaneous functional MRI (fMRI) and electroencephalography (EEG) in awake subjects at rest with eyes closed. Spontaneous power fluctuations of electrical rhythms were determined for multiple discrete frequency bands, and associated fMRI signal modulations were mapped on a voxel-by-voxel basis. There was little positive correlation of localized brain activity with alpha power (8–12 Hz), but strong and widespread negative correlation in lateral frontal and parietal cortices that are known to support attentional processes. Power in a 17–23 Hz range of beta activity was positively correlated with activity in retrosplenial, temporo-parietal, and dorsomedial prefrontal cortices. This set of areas has previously been characterized by high but coupled metabolism and blood flow at rest that decrease whenever subjects engage in explicit perception or action. The distributed patterns of fMRI activity that were correlated with power in different EEG bands overlapped strongly with those of functional connectivity, i.e., intrinsic covariations of regional activity at rest. This result indicates that, during resting wakefulness, and hence the absence of a task, these areas constitute separable and dynamic functional networks, and that activity in these networks is associated with distinct EEG signatures. Taken together with studies that have explicitly characterized the response properties of these distributed cortical systems, our findings may suggest that alpha oscillations signal a neural baseline with “inattention” whereas beta rhythms index spontaneous cognitive operations during conscious rest.
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“This extended system is consistent with previous resting-state correlation studies (28,45) and has been dubbed by us the task-positive network (28).”
From Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems (2006) · cites this paper as [45]
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Metadata
- Authors
- Laufs, H., Krakow, K., Sterzer, P., Eger, E., Beyerle, A., Salek-Haddadi, A., & Kleinschmidt, A.
- Affiliations
- Goethe University Frankfurt (DE)
- Cognitive Neurology Unit, Department of Neurology, J. W. Goethe University, Theodor-Stern-Kai 7, D-60590 Frankfurt am Main, Germany; and Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2003-09-04
- Volume
- 100
- Issue
- 19
- Pages
- 11053-11058
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC196925
- OpenAlex
- W2153394220
- Cited by
- 1,028
- References
- 37
- Citations by year
- 2026: 27 · 2025: 28 · 2024: 33 · 2023: 28 · 2022: 39 · 2021: 67 · 2020: 44 · 2019: 43 · 2018: 42 · 2017: 44 · 2016: 51 · 2015: 45 · 2014: 60 · 2013: 67 · 2012: 67
- FWCI
- 11.89
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Volkswagen Foundation
- Bundesministerium für Bildung und Forschung
- 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 › Mind wandering and attention
- Keywords
- resting state, spontaneous brain activity, alpha oscillations, beta oscillations, functional connectivity, default mode network, attention, frontal and parietal cortex, dorsomedial prefrontal cortex, temporoparietal cortex, retrosplenial cortex, inattention
- MeSH terms
- Attention, Brain, Cognition, Electroencephalography, Humans, Magnetic Resonance Imaging
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