The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Electrophysiological signatures of resting state networks in the human brain
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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 [159]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
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
Self-citationA 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
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
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-citationNeuronal 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
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).
Cited by
Sorted by citations
Items 601–700 of 1,001
Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality
Studer, B., Pedroni, A., & Rieskamp, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0076861 · Cited by 52
Cheng, Y., Xu, J., Arnone, D., Nie, B., Yu, H., Jiang, H., Bai, Y., Luo, C., Campbell, R. A. A., Shan, B., et al. (2016) · Psychological Medicine · doi:10.1017/s0033291716002440 · Cited by 51
Neural and metabolic basis of dynamic resting state fMRI
Thompson, G. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.010 · Cited by 57
Presbycusis Disrupts Spontaneous Activity Revealed by Resting-State Functional MRI
Chen, Y.-C., Chen, H.-Y., Jiang, L., Bo, F., Xu, J.-J., Mao, C.-N., Salvi, R., Yin, X.-D., Lu, G., & Gu, J.-P. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00044 · Cited by 48
Antiphase synchronization in multiplex networks with attractive and repulsive interactions
Chowdhury, S. N., Rakshit, S., Buldú, J. M., Ghosh, D., & Hens, C. (2021) · Physical review. E · doi:10.1103/physreve.103.032310 · Cited by 52
Meditation training modulates brain electric microstates and felt states of awareness
Zanesco, A. P., Skwara, A. C., King, B. G., Powers, C., Wineberg, K., & Saron, C. D. (2021) · Human Brain Mapping · doi:10.1002/hbm.25430 · Cited by 55
Clancy, K. J., Andrzejewski, J. A., Simon, J., Ding, M., Schmidt, N. B., & Li, W. (2020) · eNeuro · doi:10.1523/eneuro.0053-20.2020 · Cited by 53
Benschop, L., Poppa, T., Medani, T., Shahabi, H., Baeken, C., Leahy, R. M., Pizzagalli, D. A., & Vanderhasselt, M. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.081 · Cited by 51
Altered functional brain networks in Prader–Willi syndrome
Zhang, Y., Zhao, H., Qiu, S., Tian, J., Wen, X., Miller, J. L., von Deneen, K. M., Zhou, Z., Gold, M. S., & Liu, Y. (2013) · NMR in Biomedicine · doi:10.1002/nbm.2900 · Cited by 50
Michels, L., Muthuraman, M., Lüchinger, R., Martin, E., Anwar, A. R., Raethjen, J., Brandeis, D., & Siniatchkin, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.030 · Cited by 52
Resting-state Modulation of Alpha Rhythms by Interference with Angular Gyrus Activity
Capotosto, P., Babiloni, C., Romani, G. L., & Corbetta, M. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00460 · Cited by 53
Self-citationKEIL, J. E., Pomper, U., & Senkowski, D. (2015) · Cortex · doi:10.1016/j.cortex.2015.10.023 · Cited by 51
Lewis, C., Bosman, C. A., Womelsdorf, T., & Fries, P. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1513773113 · Cited by 51
Task-positive and task-negative networks and their relation to depression: EEG beamformer analysis
Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Tamozhnikov, S. S., & Сапрыгин, А. Е. (2016) · Behavioural Brain Research · doi:10.1016/j.bbr.2016.03.033 · Cited by 54
Smit, D. J. A., de Geus, E. J. C., Boersma, M., Boomsma, D. I., & Stam, C. J. (2016) · Brain Connectivity · doi:10.1089/brain.2015.0359 · Cited by 55
EEG topographies provide subject-specific correlates of motor control
Pirondini, E., Coscia, M., Minguillón, J., Millán, J. D. R., Ville, D. V. D., & Micera, S. (2017) · Scientific Reports · doi:10.1038/s41598-017-13482-1 · Cited by 49
Resting-State NIRS–EEG in Unresponsive Patients with Acute Brain Injury: A Proof-of-Concept Study
Othman, M., Bhattacharya, M., Møller, K., Kjeldsen, S., Grand, J., Kjærgaard, J., Dutta, A., & Kondziella, D. (2020) · Neurocritical Care · doi:10.1007/s12028-020-00971-x · Cited by 53
Mantini, D., Caulo, M., Ferretti, A., Romani, G. L., & Tartaro, A. (2009) · Radiology · doi:10.1148/radiol.2533090602 · Cited by 50
Self-citationAging affects medial but not anterior frontal learning-related theta oscillations
van de Vijver, I., Cohen, M. X., & Ridderinkhof, K. R. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.09.006 · Cited by 48
Ebisch, S. J. H., Perrucci, M. G., Mercuri, P., Romanelli, R., Mantini, D., Romani, G. L., Colom, R., & Saggino, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.04.053 · Cited by 53
Self-citationCharacterization of resting state activity in MCI individuals
Esposito, R., Mosca, A., Pieramico, V., Cieri, F., Cera, N., & Sensi, S. L. (2013) · PeerJ · doi:10.7717/peerj.135 · Cited by 51
Lee, D., Lee, J., Lee, J. E., & Jung, Y. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.02.005 · Cited by 52
Pievani, M., Pini, L., Ferrari, C., Pizzini, F. B., Galazzo, I. B., Cobelli, C., Cotelli, M., Manenti, R., & Frisoni, G. B. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161105 · Cited by 52
Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales
Timme, N. M., Ito, S., Myroshnychenko, M., Yeh, F.-C., Hiolski, E. M., Hottowy, P., & Beggs, J. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0115764 · Cited by 50
Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study
Yu, Q., Wu, L., Bridwell, D. A., Erhardt, E. B., Du, Y., He, H., Chen, J., Liu, P., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Pearlson, G. D., et al. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00476 · Cited by 49
Empirical Mode Decomposition and its Extensions Applied to EEG Analysis: A Review
Sweeney‐Reed, C. M., Nasuto, S. J., Vieira, M. F., & Andrade, A. D. O. (2018) · Advances in Data Science and Adaptive Analysis · doi:10.1142/s2424922x18400016 · Cited by 51
Neurophysiological correlates of Avolition-apathy in schizophrenia: A resting-EEG microstates study
Giordano, G. M., Koenig, T. W., Mucci, A., Vignapiano, A., Amodio, A., Lorenzo, G. D., Siracusano, A., Bellomo, A., Altamura, M., Monteleone, P., et al. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.08.031 · Cited by 49
Modeling Effective Connectivity in High-Dimensional Cortical Source Signals
Wang, Y., Ting, C., & Ombao, H. (2016) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2016.2600023 · Cited by 48
Gaining insight into the neural basis of resting-state fMRI signal
Ma, Z., Zhang, Q., Tu, W., & Zhang, N. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.118960 · Cited by 48
Functional neuroimaging abnormalities in idiopathic generalized epilepsy
McGill, M. L., Devinsky, O., Wang, X., Quinn, B. T., Pardoe, H., Carlson, C., Butler, T., Kuzniecky, R., & Thesen, T. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.10.008 · Cited by 47
Ritter, P., Freyer, F., Curio, G., & Villringer, A. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.026 · Cited by 48
Intrinsically organized network for face perception during the resting state
Zhang, H., Tian, J., Liu, J., Li, J., & Lee, K. (2009) · Neuroscience Letters · doi:10.1016/j.neulet.2009.02.054 · Cited by 48
Mancuso, L., Uddin, L. Q., Nani, A., Costa, T., & Cauda, F. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.07.004 · Cited by 47
Topological Fractionation of Resting-State Networks
Ding, J.-R., Liao, W., Zhang, Z., Mantini, D., Xu, Q., Wu, G., Lu, G., & Chen, H. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026596 · Cited by 47
Self-citationNeural networks related to pro-saccades and anti-saccades revealed by independent component analysis
Domagalik, A., Beldzik, E., Fąfrowicz, M., Ogińska, H., & Marek, T. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.006 · Cited by 51
Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues
Esposito, F., Aragri, A., Piccoli, T., Tedeschi, G., Goebel, R., & Salle, F. D. (2009) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2009.01.007 · Cited by 47
Balsters, J. H., O’Connell, R. G., Galli, A., Nolan, H., Greco, E., Kilcullen, S. M., Bokde, A. L. W., Lai, R. Y. K., Upton, N., & Robertson, I. H. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.03.004 · Cited by 48
Adolescent resting state networks and their associations to schizotypal trait expression
Lagioia (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00035 · Cited by 52
Kazemi, R., Rostami, R., Khomami, S., Horáček, J., Brunovský, M., Novák, T., & Fitzgerald, P. B. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.04.061 · Cited by 46
Resting-State Brain Anomalies in Type 2 Diabetes: A Meta-Analysis
Xia, W., Chen, Y., & Ma, J. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00014 · Cited by 47
Are Migraine With and Without Aura Really Different Entities?
Kincses, Z. T., Veréb, D., Faragó, P., Tóth, E. M., Kocsis, K., Kincses, B., Király, A., Bozsik, B., Párdutz, Á., Szok, D., et al. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00982 · Cited by 48
Speech Perception from a Neurophysiological Perspective
Giraud, A., & Poeppel, D. (2012) · Springer handbook of auditory research · doi:10.1007/978-1-4614-2314-0_9 · Cited by 51
Su, Q., Yao, D., Jiang, M., Liu, F., Jiang, J., Xu, C., Dai, Y., Yu, M., Long, L., Li, H., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099273 · Cited by 48
EEG-defined functional microstates as basic building blocks of mental processes
Lehmann, D., & Michel, C. M. (2010) · Clinical Neurophysiology · doi:10.1016/j.clinph.2010.11.003 · Cited by 54
Zhang, S., Tian, S., Chattun, M. R., Tang, H., Yan, R., Bi, K., Yao, Z., & Lü, Q. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.01.006 · Cited by 48
Electroencephalography resting‐state networks in people with Stroke
Snyder, D. B., Schmit, B. D., Hyngstrom, A. S., & Beardsley, S. A. (2021) · Brain and Behavior · doi:10.1002/brb3.2097 · Cited by 55
Benchmarking methods for mapping functional connectivity in the brain
Liu, Z.-Q., Luppi, A. I., Hansen, J. Y., Tian, Y., Zalesky, A., Yeo, B. T. T., Fulcher, B., & Mišić, B. (2025) · Nature Methods · doi:10.1038/s41592-025-02704-4 · Cited by 55
Effect of scanner acoustic background noise on strict resting-state fMRI
Rondinoni, C., Amaro, E., Cendes, F., dos Santos, A. C., & Salmón, C. E. G. (2013) · Brazilian Journal of Medical and Biological Research · doi:10.1590/1414-431x20132799 · Cited by 46
Zhou, B., Wang, J., Huang, Y., Yang, Y.-S., Gong, Q., & Zhou, D. (2013) · Journal of Neuro-Ophthalmology · doi:10.1097/wno.0b013e31828f69e5 · Cited by 46
Yan, H. J., Zhang, Y., Chen, H., Wang, Y., & Liu, Y. (2013) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617712001580 · Cited by 46
Wiesmann, M., Roelofs, M., Lugt, R. V. D., Heerschap, A., Kiliaan, A. J., & Claassen, J. A. H. R. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16667364 · Cited by 45
After-effects of transcranial alternating current stimulation on evoked delta and theta power
Wischnewski, M., & Schutter, D. J. L. G. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.08.029 · Cited by 45
Pietro, F. D., Lee, B., & Henderson, L. A. (2020) · Human Brain Mapping · doi:10.1002/hbm.25087 · Cited by 47
Temporal coding in the auditory cortex
Arnal, L. H., Poeppel, D., & Giraud, A. (2015) · Handbook of clinical neurology · doi:10.1016/b978-0-444-62630-1.00005-6 · Cited by 45
Pathophysiology of ADHD and associated problems—starting points for NF interventions?
Albrecht, B., Uebel, H., Gevensleben, H., & Rothenberger, A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00359 · Cited by 49
EEG coherence: topography and frequency structure
Chorlian, D. B., Rangaswamy, M., & Bernice Porjesz, A. (2009) · Experimental Brain Research · doi:10.1007/s00221-009-1936-9 · Cited by 46
Vanneste, S., Joos, K., Ost, J., & De Ridder, D. (2018) · Neurobiology of Stress · doi:10.1016/j.ynstr.2016.11.003 · Cited by 45
Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics
Chang, C., & Chen, J. E. (2021) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2021.100279 · Cited by 45
Férat, V., Arns, M., Deiber, M., Hasler, R., Perroud, N. A., Michel, C. M., & Ros, T. (2021) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2021.11.006 · Cited by 44
Lieberman, J. M., Rabellino, D., Densmore, M., Frewen, P., Steyrl, D., Scharnowski, F., Théberge, J., Neufeld, R. W. J., Schmahl, C. G., Jetly, R., et al. (2023) · Brain and Behavior · doi:10.1002/brb3.2883 · Cited by 49
The Role of Rhythmic Neural Synchronization in Rest and Task Conditions
Deco, G., Buehlmann, A., Masquelier, T., & Hugues, E. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00004 · Cited by 44
Operational Architectonics Methodology for EEG Analysis: Theory and Results
Fingelkurts, A. A., & Fingelkurts, A. A. (2013) · Neuromethods · doi:10.1007/7657_2013_60 · Cited by 43
Distinctive time-lagged resting-state networks revealed by simultaneous EEG-fMRI
Feige, B., Spiegelhalder, K., Kiemen, A., Bosch, O. G., van Elst, L. T., Hennig, J., Seifritz, E., & Riemann, D. W. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.027 · Cited by 46
Alba, G., Vila, J., Solaz, B. R., Montoya, P., & Muñoz, M. Á. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00064 · Cited by 53
Resting state networks in empirical and simulated dynamic functional connectivity
Glomb, K., Ponce‐Alvarez, A., Gilson, M., Ritter, P., & Deco, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.065 · Cited by 42
Brain electrical activities of dancers and fast ball sports athletes are different
Ermutlu, N., Yücesir, İ., Eskikurt, G., Temel, T., & İşoĝlu-Alkaç, Ü. (2014) · Cognitive Neurodynamics · doi:10.1007/s11571-014-9320-2 · Cited by 45
Extraversion and anterior vs. posterior DMN activity during self-referential thoughts
Knyazev, G. G. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00348 · Cited by 47
Weaver, K. E., Wander, J. D., Ko, A. L., Casimo, K., Grabowski, T. J., Ojemann, J. G., & Darvas, F. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.043 · Cited by 44
Bauer, R., & Gharabaghi, A. (2015) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2015.00021 · Cited by 43
On the “Dependence” of “Independent” Group EEG Sources; an EEG Study on Two Large Databases
Congedo, M., John, R. E., Ridder, D. D., Prichep, L. S., & Isenhart, R. (2009) · Brain Topography · doi:10.1007/s10548-009-0113-6 · Cited by 47
Ylipaavalniemi, J., Savia, E., Malinen, S., Hari, R., Vigário, R., & Samuel Kaski, A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.03.056 · Cited by 44
Lu, F., Zhou, J., Zhang, J., Xiang, Y., Zhang, J., Liu, Q., Wang, X., & Yuan, Z. (2015) · PLoS ONE · doi:10.1371/journal.pone.0145668 · Cited by 44
Wu, G., & Marinazzo, D. (2016) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2015.0190 · Cited by 46
Structural Brain Network Changes across the Adult Lifespan
Liu, K., Yao, S., Chen, K., Zhang, J., Yao, L., Li, K., Jin, Z., & Guo, X. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00275 · Cited by 45
Transition from rest to movement: Brain correlates revealed by functional connectivity
Treserras, S., Boulanouar, K., Conchou, F., Simonetta‐Moreau, M., Berry, I., Celsis, P., Chollet, F., & Loubinoux, I. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.016 · Cited by 45
Aberrant Functional Connectivity of Resting State Networks in Transient Ischemic Attack
Li, R., Wang, S., Zhu, L., Guo, J., Zeng, L., Gong, Q., He, L., & Chen, H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071009 · Cited by 43
Naturalistic stimuli: A paradigm for multiscale functional characterization of the human brain
Zhang, Y., Kim, J., Brang, D., & Liu, Z. (2021) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2021.100298 · Cited by 49
Nicholson, A. A., Densmore, M., Frewen, P., Neufeld, R. W. J., Théberge, J., Jetly, R., Lanius, R. A., & Ros, T. (2023) · Brain Communications · doi:10.1093/braincomms/fcad068 · Cited by 43
Thalamic resting-state functional connectivity: disruption in patients with type 2 diabetes
Chen, Y., Xia, W., Qian, C., Ding, J., Ju, S., & Teng, G. (2015) · Metabolic Brain Disease · doi:10.1007/s11011-015-9700-2 · Cited by 44
Narayanan, B., Soh, P., Calhoun, V. D., Ruaño, G., Kocherla, M., Windemuth, A., Clementz, B. A., Tamminga, C. A., Sweeney, J. A., Keshavan, M. S., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.76 · Cited by 45
Braga, R. M., & Leech, R. (2015) · The Neuroscientist · doi:10.1177/1073858415585730 · Cited by 42
Endogenous Neuromodulation at Infralow Frequencies
Othmer, S., Othmer, S. F., Kaiser, D. A., & Putman, J. A. (2013) · Seminars in Pediatric Neurology · doi:10.1016/j.spen.2013.10.006 · Cited by 46
Le réseau cérébral par défaut : rôle cognitif et perturbations dans la pathologie
Mevel, K., Grassiot, B., Chételat, G., Defer, G. L., Desgranges, B., & Eustache, F. (2010) · Revue Neurologique · doi:10.1016/j.neurol.2010.01.008 · Cited by 47
Electrophysiological signatures of spontaneous BOLD fluctuations in macaque prefrontal cortex
Hutchison, R. M., Hashemi, N., Gati, J. S., Menon, R. S., & Everling, S. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.062 · Cited by 43
Altered self-referential network in resting-state amnestic type mild cognitive impairment
Bai, F., Shi, Y., Yuan, Y., Wang, Y., Yue, C., Teng, Y., Wu, D., Zhang, Z., Jia, J., & Zhang, Z. (2011) · Cortex · doi:10.1016/j.cortex.2011.02.011 · Cited by 43
Cellular and circuit models of increased resting-state network gamma activity in schizophrenia
White, R. S., & Siegel, S. J. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.11.011 · Cited by 44
Cantou, P., Platel, H., Desgranges, B., & Groussard, M. (2017) · Journal of Chemical Neuroanatomy · doi:10.1016/j.jchemneu.2017.08.003 · Cited by 44
Pirondini, E., Babadi, B., Obregon-Henao, G., Lamus, C., Malik, W. Q., Hämäläinen, M., & Purdon, P. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2739824 · Cited by 45
Lateral prefrontal cortex lesion impairs regulation of internally and externally directed attention
Kam, J. W. Y., Solbakk, A., Endestad, T., Meling, T. R., & Knight, R. T. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.063 · Cited by 41
Lim, J., Kim, H., Jeon, C., & Cho, S. (2018) · Complementary Therapies in Clinical Practice · doi:10.1016/j.ctcp.2018.04.008 · Cited by 43
Test‐retest reliability of EEG network characteristics in infants
van der Velde, B., Haartsen, R., & Kemner, C. (2019) · Brain and Behavior · doi:10.1002/brb3.1269 · Cited by 43
Frequency cluster formation and slow oscillations in neural populations with plasticity
Röhr, V., Berner, R., Lameu, E. L., Popovych, O. V., & Yanchuk, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225094 · Cited by 42
Aberrant Resting-State Brain Function in Adolescent Depression
Mao, N., Che, K., Chu, T., Li, Y., Wang, Q., Liu, M., Ma, H., Wang, Z., Lin, F., Wang, B., et al. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01784 · Cited by 43
Ramkumar, P., Parkkonen, L. T., Hari, R., & Hyvärinen, A. (2011) · Human Brain Mapping · doi:10.1002/hbm.21303 · Cited by 45
Age differences in resting state EEG and their relation to eye movements and cognitive performance
Stacey, J. E., Crook‐Rumsey, M., Sumich, A. L., Howard, C. J., Crawford, T. J., Livne, K., Lenzoni, S., & Badham, S. P. (2021) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2021.107887 · Cited by 46
Palombit, A., Silvestri, E., Volpi, T., Aiello, M., Cecchin, D., Bertoldo, A., & Corbetta, M. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119280 · Cited by 43
Self-citationAutomatic selection of resting-state networks with functional magnetic resonance imaging
Storti, S. F., Formaggio, E., Nordio, R., Manganotti, P., Fiaschi, A., Bertoldo, A., & TOFFOLO, G. M. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00072 · Cited by 44
Autoregressive model in the Lp norm space for EEG analysis
Li, P., Wang, X., Li, F., Zhang, R., Ma, T., Peng, Y., Lei, X., Tian, Y., Guo, D., Liu, T., et al. (2014) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.11.007 · Cited by 42
Henseler, I., Krüger, S., Dechent, P., & Gruber, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.056 · Cited by 50
Metadata
- 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)
- 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
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review