Cited by 1,938Functional Brain Connectivity StudiesNeural dynamics and brain functionAdvanced MRI Techniques and Applications

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Electrophysiological signatures of resting state networks in the human brain

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Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., Corbetta, M.·2007·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.0700668104PMC PMC1941820

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Abstract

Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1–80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.

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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
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Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Self-citation
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576
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
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
Fast and robust fixed-point algorithms for independent component analysis
Hyvärinen, A. (1999) · IEEE Transactions on Neural Networks · doi:10.1109/72.761722 · Cited by 6,304
The brainweb: phase synchronization and large-scale integration
Varela, F., Lachaux, J.-P., Rodriguez, E., & Martinerie, J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35067550 · Cited by 4,761

Show all 53 references

Research works printed but not linked: 1

D Cordes, VM Haughton, K Arfanakis, JD Carew, PA Turski, CH Moritz, MA Quigley, ME Meyerand Am J Neuroradiol 22, 1326–1333 (2001).

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Self-citation
Clinical evaluation of adhesively placed Cerec endo-crowns after 2 years--preliminary results.
Bindl, A., & MÖRMANN, W. H. (1999) · PubMed · Cited by 279
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Authors: Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., & Corbetta, M.
Affiliations: University of Chieti-Pescara (IT)
Institute of Advanced Biomedical Technologies and
Washington University in St. Louis (US)
ORCID: Mantini, D.
Perrucci, M. G.
Romani, G. L.
Corbetta, M.
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2007-08-07
Volume: 104
Issue: 32
Pages: 13170-13175
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.0700668104
PMC: PMC1941820
OpenAlex: W2063294564
Cited by: 1,938
References: 53
Citations by year: 2026: 54 · 2025: 68 · 2024: 87 · 2023: 72 · 2022: 110 · 2021: 140 · 2020: 117 · 2019: 118 · 2018: 112 · 2017: 127 · 2016: 117 · 2015: 107 · 2014: 117 · 2013: 140 · 2012: 112
FWCI: 38.14
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Proceedings of the National Academy of Sciences (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Lirias (submittedVersion, other-oa)
Padua Research Archive (University of Padova) (submittedVersion, other-oa)
Funders: European Commission
National Institutes of Health
National Institute of Mental Health (R01 MH 71920-06, R01MH071920)
National Institute of Neurological Disorders and Stroke (R01NS048013, NS48013)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords: resting-state networks, intrinsic brain activity, EEG oscillations, neural oscillations, independent component analysis, large-scale brain networks, simultaneous EEG-fMRI
MeSH terms: Adult, Brain, Electroencephalography, Humans, Magnetic Resonance Imaging, Male, Oxygen

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Electrophysiological signatures of resting state networks in the human brain

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