Cited by 1,028Functional Brain Connectivity StudiesNeural dynamics and brain functionMind wandering and attention

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Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest

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Laufs, H., Krakow, K., Sterzer, P., Eger, E., Beyerle, A., Salek-Haddadi, A., Kleinschmidt, A.·2003·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.1831638100PMC PMC196925

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Abstract

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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Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
Neurophysiological investigation of the basis of the fMRI signal
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001) · Nature · doi:10.1038/35084005 · Cited by 6,551
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Über das Elektrenkephalogramm des Menschen
Berger, H. (1929) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/bf01797193 · Cited by 4,266
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.
Kwong, K. K., Belliveau, J. W., Chesler, D. A., Goldberg, I. E., Weisskoff, R. M., Poncelet, B. P., Kennedy, D. N., Hoppel, B. E., Cohen, M. S., & Turner, R. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5675 · Cited by 4,212
Searching for a baseline: Functional imaging and the resting human brain
Gusnard, D. A., & Raichle, M. E. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094500 · Cited by 3,371
Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function
Gusnard, D. A., Akbudak, E., Shulman, G. L., & Raichle, M. E. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.071043098 · Cited by 2,997

Show all 37 references

Research works printed but not linked: 5

Vogel, F. (1962) Dtsch. Z. Nervenheilkd. 184, 137–173.13997623
Cordes, D., Haughton, V. M., Arfanakis, K., Carew, J. D., Turski, P. A., Moritz, C. H., Quigley, M. A. & Meyerand, M. E. (2001) AJNR Am. J. Neuroradiol. 22, 1326–1333.11498421
McGuire, P. K., Paulesu, E., Frackowiak, R. S. & Frith, C. D. (1996) NeuroReport 7, 2095–2099.8930966
Adrian, E. D. & Matthews, B. H. C. (1934) Brain 57, 356.
Jung, R. (1953) in Handbuch der Inneren Medizin, eds. von Bergmann, G., Frey, W. & Schwiegk, H. (Springer, Berlin), Vol. 1, pp. 1216–1325.

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Bibliography
(2023) · The MIT Press eBooks · doi:10.7551/mitpress/13829.003.0012
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Alhajri, N. (2023) · doi:10.54337/aau528835322
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Liu, T. T. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-91688-2.00005-9
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Prior probability cues bias sensory encoding with increasing task exposurePreprint
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Self-citation
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Wen, Z., He, Y., & Huang, X. (2024) · Neuroreport · doi:10.1097/wnr.0000000000002068
Reviewer #2 (Public Review): Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replication
Das, A., & Menon, V. (2024) · eLife · doi:10.7554/elife.99018.1.sa0
eLife Assessment: Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replication
Swann, N. C. (2024) · eLife · doi:10.7554/elife.99018.1.sa2
Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replicationPreprint
Das, A., & Menon, V. (2024) · eLife · doi:10.7554/elife.99018.1
Reviewer #1 (Public Review): Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replication
Das, A., & Menon, V. (2024) · eLife · doi:10.7554/elife.99018.1.sa1
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Das, A., & Menon, V. (2024) · eLife · doi:10.7554/elife.99018.2
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Marchesi, S., Spatola, N., & Wykowska, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-65483-1_2
Social functioning and frontal alpha asymmetry in schizophrenia
Farina, E. A., Assaf, M., Corbera, S., Choi, J., Yantz, C. L., & Chen, C. A. (2025) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2025.01.006
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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
ORCID: Laufs, H.
Krakow, K.
Sterzer, P.
Eger, E.
Kleinschmidt, A.
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
DOI: 10.1073/pnas.1831638100
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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Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest

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