The brain's resting-state activity is shaped by synchronized cross-frequency coupling of neural oscillations
Open accessAbstract
Functional imaging of the resting brain consistently reveals broad motifs of correlated blood oxygen level dependent (BOLD) activity that engages cerebral regions from distinct functional systems. Yet, the neurophysiological processes underlying these organized, large-scale fluctuations remain to be uncovered. Using magnetoencephalography (MEG) imaging during rest in 12 healthy subjects we analyze the resting state networks and their underlying neurophysiology. We first demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower spontaneous fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signaling for long-range brain communication.
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Electrophysiological infraslow fluctuations are believed to coordinate large-scale intrinsic connectivity network organization and long-range information exchange.
“and are believed to coordinate large-scale ICN organization and long-range information exchange [68, 83–91].”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [90]
The Introduction and the Discussion’s ‘Neural Network Formation with Synchronized Gating’ section support a role for synchronized slower oscillations in resting-state network formation and long-range communication. But the Introduction identifies the studied low-frequency components as delta (2–4 Hz), theta (4–8 Hz), and alpha (8–12 Hz); it does not establish the claim specifically for infraslow fluctuations. Page numbers are unavailable in our copy. (LLM, conf=0.88)
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Cites
Newey, W. K., & West, K. D. (1987) · Econometrica · doi:10.2307/1913610 · Cited by 16,936 · see citing works
A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix
Newey, W. K., & West, K. D. (1986) · National Bureau of Economic Research · doi:10.3386/t0055 · Cited by 12,682 · see citing works
The organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00338.2011 · Cited by 9,182 · see citing works
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304 · see citing works
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576 · see citing works
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 6,542 · see citing works
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150 · see citing works
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 · see citing works
A mechanism for cognitive dynamics: neuronal communication through neuronal coherence.
Fries, P. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.08.011 · Cited by 4,284 · see citing works
Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential
Leski, S., Lindén, H., Tetzlaff, T., Pettersen, K. H., & Einevoll, G. T. (2013) · PubMed Central · doi:10.18154/rwth-conv-084442 · Cited by 3,662 · see citing works
Brainstorm: A User-Friendly Application for MEG/EEG Analysis
Tadel, F., Baillet, S., Mosher, J. C., Pantazis, D., & Leahy, R. M. (2011) · Computational Intelligence and Neuroscience · doi:10.1155/2011/879716 · Cited by 3,625 · see citing works
Self-citationToward discovery science of human brain function
Biswal, B. B., Mennes, M., Zuo, X.-N., Gohel, S., Kelly, C., Smith, S. M., Beckmann, C. F., Adelstein, J. S., Buckner, R. L., Colcombe, S., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911855107 · Cited by 2,970 · see citing works
Mechanisms of Gamma Oscillations
Buzsáki, G., & Wang, X.-J. (2012) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150444 · Cited by 2,796 · see citing works
High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex
Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M., & Knight, R. T. (2006) · Science · doi:10.1126/science.1128115 · Cited by 2,650 · see citing works
Neuronal Synchrony: A Versatile Code for the Definition of Relations?
Singer, W. (1999) · Neuron · doi:10.1016/s0896-6273(00)80821-1 · Cited by 2,581 · see citing works
Buckner, R. L., Snyder, A. Z., Shannon, B. J., LaRossa, G., Sachs, R., Fotenos, A. F., Sheline, Y. I., Klunk, W. E., Mathis, C. A., Morris, J. C., et al. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.2177-05.2005 · Cited by 2,140 · see citing works
The functional role of cross-frequency coupling
Canolty, R. T., & Knight, R. T. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.09.001 · Cited by 2,101 · see citing works
Evidence for a Frontoparietal Control System Revealed by Intrinsic Functional Connectivity
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90355.2008 · Cited by 1,869 · see citing works
Baillet, S., Mosher, J. C., & Leahy, R. M. (2001) · IEEE Signal Processing Magazine · doi:10.1109/79.962275 · Cited by 1,691 · see citing works
Self-citationLakatos, P., Shah, A. S., Knuth, K. H., Ulbert, I., Karmos, G., & Schroeder, C. E. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00263.2005 · Cited by 1,241 · see citing works
Large-scale cortical correlation structure of spontaneous oscillatory activity
Hipp, J. F., Hawellek, D. J., Corbetta, M., Siegel, M., & Engel, A. K. (2012) · Nature Neuroscience · doi:10.1038/nn.3101 · Cited by 1,113 · see citing works
Cross-frequency coupling between neuronal oscillations
Jensen, O., & Colgin, L. L. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.05.003 · Cited by 991 · see citing works
Haider, B., Duque, A., Hasenstaub, A. R., & McCormick, D. A. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.5297-05.2006 · Cited by 962 · see citing works
The role of the thalamus in the flow of information to the cortex
Sherman, S. M., & Guillery, R. W. (2002) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.2002.1161 · Cited by 938 · see citing works
Investigating the electrophysiological basis of resting state networks using magnetoencephalography
Brookes, M. J., Woolrich, M., Luckhoo, H., Price, D., Hale, J. R., Stephenson, M. C., Barnes, G. R., Smith, S. M., & Morris, P. G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1112685108 · Cited by 938 · see citing works
Theta-gamma coupling increases during the learning of item-context associations
Tort, A. B. L., Komorowski, R. W., Manns, J. R., Kopell, N. J., & Eichenbaum, H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911331106 · Cited by 919 · see citing works
Tort, A. B. L., Kramer, M., Thorn, C. A., Gibson, D. J., Kubota, Y., Graybiel, A. M., & Kopell, N. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810524105 · Cited by 842 · see citing works
Short frontal lobe connections of the human brain
Catani, M., Dell’Acqua, F., Vergani, F., Malik, F., Hodge, H., Roy, P. K., Valabrègue, R., & de Schotten, M. T. (2011) · Cortex · doi:10.1016/j.cortex.2011.12.001 · Cited by 789 · see citing works
Top-down processing mediated by interareal synchronization
von Stein, A., Chiang, C., & Peter König, B. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.26.14748 · Cited by 722 · see citing works
Temporal dynamics of spontaneous MEG activity in brain networks
de Pasquale, F., Della Penna, S., Snyder, A. Z., Lewis, C., Mantini, D., Marzetti, L., Belardinelli, P., Ciancetta, L., Pizzella, V., Romani, G. L., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0913863107 · Cited by 698 · see citing works
Raichle, M. E. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0019 · Cited by 672 · see citing works
A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG
Huang, M., Mosher, J. C., & Leahy, R. M. (1999) · Physics in Medicine and Biology · doi:10.1088/0031-9155/44/2/010 · Cited by 615 · see citing works
Shmuel, A., & Leopold, D. A. (2008) · Human Brain Mapping · doi:10.1002/hbm.20580 · Cited by 584 · see citing works
The chirplet transform: physical considerations
Mann, S., & Haykin, S. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.482123 · Cited by 561 · see citing works
Suppression of Interference and Artifacts by the Signal Space Separation Method
Taulu, S., Kajola, M., & Simola, J. (2004) · Brain Topography · doi:10.1023/b:brat.0000032864.93890.f9 · Cited by 541 · see citing works
Kasdin, N. J. (1995) · Proceedings of the IEEE · doi:10.1109/5.381848 · Cited by 536 · see citing works
Steriade, M., Contreras, D., Amzica, F., & Timofeev, I. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-08-02788.1996 · Cited by 404 · see citing works
Voytek, B. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00191 · Cited by 401 · see citing works
Abnormal Functional Connectivity in Children with Attention-Deficit/Hyperactivity Disorder
Tomasi, D., & Volkow, N. D. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.11.003 · Cited by 363 · see citing works
Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays
Vicente, R., Gollo, L. L., Mirasso, C. R., Fischer, I., & Pipa, G. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809353105 · Cited by 341 · see citing works
Gamma Power Is Phase-Locked to Posterior Alpha Activity
Osipova, D. V., Hermes, D., & Jensen, O. B. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003990 · Cited by 329 · see citing works
Özkurt, T. E., Butz, M., Homburger, M., Elben, S., Vesper, J., Wojtecki, L., & Schnitzler, A. (2011) · Experimental Neurology · doi:10.1016/j.expneurol.2011.02.015 · Cited by 196 · see citing works
Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures
Kramer, M. A., Tort, A. B. L., & Kopell, N. J. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.01.020 · Cited by 195 · see citing works
Ongoing physiological processes in the cerebral cortex
Leopold, D. A., & Maier, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.059 · Cited by 127 · see citing works
A critical note on the definition of phase–amplitude cross-frequency coupling
Özkurt, T. E., & Schnitzler, A. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2011.08.014 · Cited by 124 · see citing works
Rivière, D., Geffroy, D., Denghien, I., Souedet, N., & Cointepas, Y. (2009) · NeuroImage · doi:10.1016/s1053-8119(09)71720-3 · Cited by 60 · see citing works
Nolte, G., & Curio, G. (1999) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.752937 · Cited by 52 · see citing works
Smith, K. (2012) · Nature · doi:10.1038/489356a · Cited by 34 · see citing works
Paving the way for cross-site pooling of magnetoencephalography (MEG) data
Weisend, M. P., Hanlon, F. M., Montaño, R., Ahlfors, S. P., Leuthold, A., Pantazis, D., Mosher, J. C., Georgopoulos, A. P., Hämäläinen, M., & Aine, C. J. (2007) · International Congress Series · doi:10.1016/j.ics.2006.12.095 · Cited by 16 · see citing works
Cheyne, D. O., Roß, B., Stroink, G., & Weinberg, H. (2007) · Cited by 1 · see citing works
Flagged first, then by citations
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Magnetoencephalography for Brain Electrophysiology and Imaging
Baillet, S. (2017) · Nature Neuroscience · doi:10.1038/nn.4504 · Cited by 992 · see citing works
Self-citationCommunication between Brain Areas Based on Nested Oscillations
Bonnefond, M., Kästner, S., & Jensen, O. B. (2017) · eNeuro · doi:10.1523/eneuro.0153-16.2017 · Cited by 270 · see citing works
Electrophysiological Brain Connectivity: Theory and Implementation
He, B., Laura Astolfi, A., Valdes-Sosa, P. A., Marinazzo, D., Palva, S., Bénar, C., Michel, C. M., & Koenig, T. W. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2913928 · Cited by 236 · see citing works
Dynamics of large-scale electrophysiological networks: A technical review
O’Neill, G. C., Tewarie, P. K. B., Vidaurre, D., Liuzzi, L., Woolrich, M. W., & Brookes, M. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.003 · Cited by 214 · see citing works
A multi-layer network approach to MEG connectivity analysis
Brookes, M. J., Tewarie, P. K. B., Hunt, B. A. E., Robson, S. E., Gascoyne, L. E., Liddle, E. B., Liddle, P. F., & Morris, P. G. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.045 · Cited by 197 · see citing works
Deco, G., Cabral, J., Woolrich, M. W., Stevner, A. B. A., van Hartevelt, T. J., & Kringelbach, M. L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.03.023 · Cited by 193 · see citing works
Keitel, A., & Groß, J. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002498 · Cited by 173 · see citing works
IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)
Hari, R., Baillet, S., Barnes, G. R., Burgess, R. C., Forss, N., Groß, J., Hämäläinen, M., Jensen, O. B., Kakigi, R., Mauguı̀ere, F., et al. (2018) · Clinical Neurophysiology · doi:10.1016/j.clinph.2018.03.042 · Cited by 170 · see citing works
Self-citationMagnetoencephalography in Cognitive Neuroscience: A Primer
Groß, J. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.001 · Cited by 160 · see citing works
Richter, C. G., Babo-Rebelo, M., Schwartz, D., & Tallon-Baudry, C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.043 · Cited by 151 · see citing works
Liu, Q., Ganzetti, M., Wenderoth, N., & Mantini, D. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00004 · Cited by 148 · see citing works
O’Neill, G. C., Barratt, E. L., Hunt, B. A. E., Tewarie, P. K. B., & Brookes, M. J. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/21/r271 · Cited by 139 · see citing works
Connectomics of human electrophysiology
Sadaghiani, S., Brookes, M. J., & Baillet, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118788 · Cited by 113 · see citing works
Self-citationZilio, F., Gómez‐Pilar, J., Cao, S., Zhang, J., Zang, D., Qi, Z., Tan, J., Hiromi, T., Wu, X., Fogel, S. M., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117579 · Cited by 110 · see citing works
Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings
Siebenhühner, F., Wang, S. H., Arnulfo, G., Lampinen, A., Nobili, L., Palva, J. M., & Palva, S. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3000685 · Cited by 101 · see citing works
Brief segments of neurophysiological activity enable individual differentiation
da Silva Castanheira, J., Orozco Perez, H. D., Misic, B., & Baillet, S. (2021) · Nature Communications · doi:10.1038/s41467-021-25895-8 · Cited by 101 · see citing works
Self-citationCross-Frequency Coupling Based Neuromodulation for Treating Neurological Disorders
Salimpour, Y., & Anderson, W. S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00125 · Cited by 100 · see citing works
Brainstorm Pipeline Analysis of Resting-State Data From the Open MEG Archive
Niso, G., Tadel, F., Bock, E. A., Cousineau, M., Santos, A., & Baillet, S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00284 · Cited by 99 · see citing works
Self-citationTime-resolved phase-amplitude coupling in neural oscillations
Samiee, S., & Baillet, S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.051 · Cited by 90 · see citing works
Self-citationMarzetti, L., Basti, A., Chella, F., D’Andrea, A., Syrjälä, J., & Pizzella, V. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00964 · Cited by 88 · see citing works
The Detection of Phase Amplitude Coupling during Sensory Processing
Seymour, R. A., Rippon, G., & Kessler, K. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00487 · Cited by 78 · see citing works
Hsiao, F., Wang, S., Lin, Y., Fuh, J., Ko, Y., Wang, P., & Chen, W. (2017) · The Journal of Headache and Pain · doi:10.1186/s10194-017-0799-x · Cited by 77 · see citing works
Neurophysiological signatures of cortical micro-architecture
Shafiei, G., Fulcher, B., Voytek, B., Satterthwaite, T. D., Baillet, S., & Mišić, B. (2023) · Nature Communications · doi:10.1038/s41467-023-41689-6 · Cited by 75 · see citing works
Self-citationNon-linear auto-regressive models for cross-frequency coupling in neural time series
la Tour, T. D., Tallot, L., Grabot, L., Doyère, V., van Wassenhove, V., Grenier, Y., & Gramfort, A. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005893 · Cited by 76 · see citing works
Wiesman, A. I., Castanheira, J. D. S., & Baillet, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118823 · Cited by 72 · see citing works
Self-citationDimitriadis, S. I., Zouridakis, G., Rezaie, R., Abbas Babajani-feremi, A., & Papanicolaou, A. C. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.09.011 · Cited by 73 · see citing works
Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury
Antonakakis, M., Dimitriadis, S. I., Zervakis, M. E., Micheloyannis, S., Rezaie, R., Abbas Babajani-feremi, A., Zouridakis, G., & Papanicolaou, A. C. (2016) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2016.02.002 · Cited by 70 · see citing works
Shafiei, G., Baillet, S., & Mišić, B. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001735 · Cited by 72 · see citing works
Self-citationDiscriminating Valid from Spurious Indices of Phase-Amplitude Coupling
Jensen, O. B., Spaak, E., & Park, H. (2016) · eNeuro · doi:10.1523/eneuro.0334-16.2016 · Cited by 69 · see citing works
The role of the anterior nuclei of the thalamus in human memory processing
Sweeney‐Reed, C. M., Buentjen, L., Voges, J., Schmitt, F. C., Zaehle, T., Kam, J. W. Y., Kaufmann, J., Heinze, H., Hinrichs, H., Knight, R. T., et al. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.046 · Cited by 66 · see citing works
Measuring transient phase-amplitude coupling using local mutual information
Martínez-Cancino, R., Heng, J., Arnaud Delorme, A., Kreutz-Delgado, K., Sotero, R. C., & Makeig, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.034 · Cited by 64 · see citing works
Harquel, S., Bacle, T., Beynel, L., Marendaz, C., Chauvin, A., & Olivier David, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.009 · Cited by 59 · see citing works
A New Modular Brain Organization of the BOLD Signal during Natural Vision
Kim, D., Kay, K., Shulman, G. L., & Corbetta, M. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx175 · Cited by 56 · see citing works
Lee, T. L., Lee, H., & Kang, N. (2023) · npj Science of Learning · doi:10.1038/s41539-022-00152-9 · Cited by 58 · see citing works
Incorporating priors for EEG source imaging and connectivity analysis
Lei, X., Wu, T., & Valdes-Sosa, P. A. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00284 · Cited by 56 · see citing works
Turkheimer, F., Leech, R., Expert, P., Lord, L.-D., & Vernon, A. C. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.04.014 · Cited by 54 · see citing works
Learning improves decoding of odor identity with phase-referenced oscillations in the olfactory bulb
Losacco, J. T., Ramírez-Gordillo, D., Gilmer, J. I., & Restrepo, D. (2020) · eLife · doi:10.7554/elife.52583 · Cited by 50 · see citing works
Phase-amplitude coupling and epileptogenesis in an animal model of mesial temporal lobe epilepsy
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Self-citationGaining insight into the neural basis of resting-state fMRI signal
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Laminar Distribution of Phase-Amplitude Coupling of Spontaneous Current Sources and Sinks
Sotero, R. C., Bortel, A. B., Naaman, S., Mocanu, V. M., Kropf, P., Villeneuve, M. Y., & Shmuel, A. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00454 · Cited by 47 · see citing works
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 · see citing works
Default Mode Network Oscillatory Coupling Is Increased Following Concussion
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Exploring phase–amplitude coupling from primary motor cortex-basal ganglia–thalamus network model
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Dimitriadis, S. I., Laskaris, N., Simos, P. G., Fletcher, J. M., & Papanicolaou, A. C. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00163 · Cited by 41 · see citing works
Dimitriadis, S. I., López, M. E., Bruña, R., Cuesta, P., Marcos, A., Maestú, F., & Pereda, E. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00306 · Cited by 41 · see citing works
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Sotero, R. C. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005180 · Cited by 38 · see citing works
Human brain imaging with high‐density electroencephalography: Techniques and applications
Marino, M., & Mantini, D. (2024) · The Journal of Physiology · doi:10.1113/jp286639 · Cited by 38 · see citing works
The comparative performance of DBS artefact rejection methods for MEG recordings
Kandemir, A. L., Vladimir Litvak, A., & Florin, E. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117057 · Cited by 36 · see citing works
Self-citationNorthoff, G. (2017) · Consciousness and Cognition · doi:10.1016/j.concog.2017.03.006 · Cited by 36 · see citing works
Cortical oscillatory dysrhythmias in visual snow syndrome: a magnetoencephalography study
Hepschke, J. L., Seymour, R. A., He, W., Etchell, A. C., Sowman, P. F., & Fraser, C. L. (2021) · Brain Communications · doi:10.1093/braincomms/fcab296 · Cited by 34 · see citing works
Kim, J. A., & Davis, K. D. (2021) · Journal of Neurophysiology · doi:10.1152/jn.00530.2020 · Cited by 35 · see citing works
Driving working memory with frequency‐tuned noninvasive brain stimulation
Albouy, P., Baillet, S., & Zatorre, R. J. (2018) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13664 · Cited by 32 · see citing works
Self-citationDorsal and ventral cortices are coupled by cross-frequency interactions during working memory
Popov, T. G., Jensen, O. B., & Schoffelen, J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.054 · Cited by 33 · see citing works
The Menstrual Cycle Alters Resting-State Cortical Activity: A Magnetoencephalography Study
Haraguchi, R., Hoshi, H., Ichikawa, S., Hanyu, M., Nakamura, K., Fukasawa, K., Poza, J., Rodríguez-González, V., Gómez, C., & Shigihara, Y. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.652789 · Cited by 33 · see citing works
Hsiao, F., Chen, W., Pan, L. H., Liu, H., Wang, Y.-F., Chen, S., Lai, K., Coppola, G., & Wang, S. (2022) · The Journal of Headache and Pain · doi:10.1186/s10194-022-01500-1 · Cited by 33 · see citing works
Liu, Z.-Q., Shafiei, G., Baillet, S., & Mišić, B. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120276 · Cited by 30 · see citing works
Self-citationAutomated Detection of Epileptic Biomarkers in Resting-State Interictal MEG Data
Soriano, M. C., Niso, G., Clements, J. M., Ortín, S., Carrasco, S., Gudín, M., Mirasso, C. R., & Pereda, E. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00043 · Cited by 32 · see citing works
Intact Auditory Cortical Cross-Frequency Coupling in Early and Chronic Schizophrenia
Murphy, N., Ramakrishnan, N., Walker, C. P. R., Polizzotto, N. R., & Cho, R. Y. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00507 · Cited by 31 · see citing works
Wang, X., Li, L., Xu, T., & Ding, Z. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140300 · Cited by 30 · see citing works
Lowet, E., Gips, B., Roberts, M. J., Weerd, P. D., Jensen, O. B., & van der Eerden, J. P. J. M. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2004132 · Cited by 30 · see citing works
Anterior Thalamic High Frequency Band Activity Is Coupled with Theta Oscillations at Rest
Sweeney‐Reed, C. M., Zaehle, T., Voges, J., Schmitt, F. C., Buentjen, L., Borchardt, V., Walter, M., Hinrichs, H., Heinze, H., Rugg, M. D., et al. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00358 · Cited by 30 · see citing works
Hsiao, F., Chen, W., Liu, H., Wang, Y.-F., Chen, S., Lai, K., Pan, L. H., Coppola, G., & Wang, S. (2021) · Pain · doi:10.1097/j.pain.0000000000002255 · Cited by 29 · see citing works
Wang, Y., Long, Z., Cui, Q., Liu, F., Jing, X., Chen, H., Guo, X., Yan, J. H., & Chen, H.-F. (2015) · Human Brain Mapping · doi:10.1002/hbm.23037 · Cited by 28 · see citing works
Cheng, C., Wang, P., Mao, H., & Hsiao, F. (2020) · Aging · doi:10.18632/aging.102859 · Cited by 26 · see citing works
A 3D atlas of functional human brain energetic connectome based on neuropil distribution
Yu, Y., Akif, A., Hermán, P., Cao, M., Rothman, D. L., Carson, R. E., Agarwal, D., Evans, A. C., & Hyder, F. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac322 · Cited by 26 · see citing works
Roehri, N., Bréchet, L., Seeber, M., Pascual‐Leone, Á., & Michel, C. M. (2022) · Brain Topography · doi:10.1007/s10548-022-00890-4 · Cited by 25 · see citing works
Cerebral electrometabolic coupling in disordered and normal states of consciousness
Annen, J., Frasso, G., van der Lande, G., Bonin, E., Vitello, M. M., Panda, R., Sala, A., Cavaliere, C., Raimondo, F., Bahri, M. A., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112854 · Cited by 24 · see citing works
Sotero, R. C. (2015) · BioMed Research International · doi:10.1155/2015/915606 · Cited by 24 · see citing works
Characteristic oscillatory brain networks for predicting patients with chronic migraine
Hsiao, F., Chen, W., Wu, Y., Pan, L. H., Wang, Y.-F., Chen, S., Lai, K., Coppola, G., & Wang, S. (2023) · The Journal of Headache and Pain · doi:10.1186/s10194-023-01677-z · Cited by 23 · see citing works
New Cognitive Neurotechnology Facilitates Studies of Cortical–Subcortical Interactions
Min, B., Hämäläinen, M., & Pantazis, D. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.03.003 · Cited by 23 · see citing works
Beuter, A. C., Balossier, A., Vassal, F., Hemm, S., & Volpert, V. A. (2020) · Biological Cybernetics · doi:10.1007/s00422-020-00818-w · Cited by 22 · see citing works
Antonakakis, M., Dimitriadis, S. I., Zervakis, M. E., Papanicolaou, A. C., & Zouridakis, G. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00416 · Cited by 22 · see citing works
Liu, X., Chen, L., Cheng, R., Luo, T., Lv, F., Fang, W., Gong, J., & Jiang, P. (2019) · Brain Research · doi:10.1016/j.brainres.2019.03.022 · Cited by 22 · see citing works
Defining the filter parameters for phase-amplitude coupling from a bispectral point of view
Zandvoort, C. S., & Nolte, G. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.109032 · Cited by 21 · see citing works
Zhang, J., Liu, D., Qian, S., Qu, X., Zhang, P., Ding, N., & Zang, Y. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac124 · Cited by 21 · see citing works
Abnormal phase–amplitude coupling characterizes the interictal state in epilepsy
Fujita, Y., Yanagisawa, T., Fukuma, R., Ura, N., Oshino, S., & Kishima, H. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac64c4 · Cited by 20 · see citing works
Aberrant neurophysiological signaling associated with speech impairments in Parkinson’s disease
Wiesman, A. I., Donhauser, P. W., Degroot, C., Diab, S., Kousaie, S., Fon, E. A., Klein, D., Baillet, S., Villeneuve, S., & Quebec Parkinson Network (2023) · npj Parkinson s Disease · doi:10.1038/s41531-023-00495-z · Cited by 20 · see citing works
Self-citationShumbayawonda, E., Fernández, A., Hughes, M. P., & Abásolo, D. (2017) · Entropy · doi:10.3390/e19040141 · Cited by 19 · see citing works
Multiscale energy reallocation during low‐frequency steady‐state brain response
Wang, Y., Chen, W., Ye, L., Biswal, B. B., Yang, X., Zou, Q., Yang, P., Yang, Q., Wang, X., Cui, Q., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.23992 · Cited by 18 · see citing works
Dimitriadis, S. I. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.110073 · Cited by 19 · see citing works
Donaldson, P. H., Kirkovski, M., Yang, J. S. C., Bekkali, S., & Enticott, P. G. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00338.2019 · Cited by 19 · see citing works
Regional Patterns of Cortical Phase Synchrony in the Resting State
Casimo, K., Darvas, F., Wander, J. D., Ko, A. L., Grabowski, T. J., Novotny, E. J., Poliakov, A. V., Ojemann, J. G., & Weaver, K. E. (2016) · Brain Connectivity · doi:10.1089/brain.2015.0362 · Cited by 19 · see citing works
Chang, P., Lorenzo Fabrizi, D., & Fitzgerald, M. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0416-22.2022 · Cited by 18 · see citing works
Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people
Abubaker, M., Qasem, W. A., Pilátová, K., Ježdík, P., & Kvašňák, E. (2024) · Molecular Brain · doi:10.1186/s13041-024-01149-8 · Cited by 16 · see citing works
Hou, D., Wang, C., Chen, Y., Wang, W., & Du, J. (2017) · Cognitive Neurodynamics · doi:10.1007/s11571-017-9451-3 · Cited by 17 · see citing works
Hsiao, F., Chen, W., Liu, H., Wang, Y.-F., Chen, S., Lai, K., Pan, L. H., & Wang, S. (2020) · The Journal of Headache and Pain · doi:10.1186/s10194-020-01200-8 · Cited by 17 · see citing works
Coupled oscillations enable rapid temporal recalibration to audiovisual asynchrony
Lennert, T., Samiee, S., & Baillet, S. (2021) · Communications Biology · doi:10.1038/s42003-021-02087-0 · Cited by 17 · see citing works
Self-citationWang, J., Liu, Q., Tian, F., Zhou, S., Parra, M. A., Wang, H., & Yu, X. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.829755 · Cited by 17 · see citing works
Theta–gamma coupling in the prelimbic area is associated with heroin addiction
Zhu, Z., Ye, Z., Wang, H., Hua, T., Wen, Q., & Zhang, C. (2019) · Neuroscience Letters · doi:10.1016/j.neulet.2019.02.020 · Cited by 16 · see citing works
EEG phase-amplitude coupling to stratify encephalopathy severity in the developing brain
Wang, X., Liu, H., Kota, S., Das, Y., Liu, Y., Zhang, R., & Chalak, L. F. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106593 · Cited by 17 · see citing works
Low Frequency Phase-locking of Brain Signals Contribute to Efficient Face Recognition
Wang, Y., Huang, X., Yang, X., Yang, Q., Wang, X., Northoff, G., Pang, Y., Wang, C., Cui, Q., & Chen, H. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.10.024 · Cited by 16 · see citing works
Wang, Z., Cao, Q., Bai, W., Zheng, X., & Liu, T. (2021) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2021.799556 · Cited by 15 · see citing works
Rodríguez-González, V., Nùñez, P., Gómez, C., Hoshi, H., Shigihara, Y., Hornero, R., & Poza, J. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105512 · Cited by 15 · see citing works
Gait-related beta-gamma phase amplitude coupling in the subthalamic nucleus of parkinsonian patients
Farokhniaee, A., Palmisano, C., Vecchio, J. D. V. D., Pezzoli, G., Volkmann, J., & Isaias, I. U. (2024) · Scientific Reports · doi:10.1038/s41598-024-57252-2 · Cited by 15 · see citing works
Under the Mind's Hood: What We Have Learned by Watching the Brain at Work
Nobre, A. C., & van Ede, F. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0742-19.2019 · Cited by 14 · see citing works
Rosso, M., Fernández‐Rubio, G., Keller, P. E., Brattico, E., Vuust, P., Kringelbach, M. L., & Bonetti, L. (2025) · Advanced Science · doi:10.1002/advs.202413195 · Cited by 18 · see citing works
Interlayer connectivity reconstruction for multilayer brain networks using phase oscillator models
Tewarie, P. K. B., Prasse, B., Meier, J. M., Byrne, Á., Domenico, M. D., Stam, C. J., Brookes, M. J., Hillebrand, A., Daffertshofer, A., Coombes, S., et al. (2021) · New Journal of Physics · doi:10.1088/1367-2630/ac066d · Cited by 14 · see citing works
Wiafe, S.-L., Asante, N. O., Calhoun, V. D., & Faghiri, A. (2025) · Brain Connectivity · doi:10.1177/21580014251376733 · Cited by 13 · see citing works
Genuine cross-frequency coupling networks in human resting-state electrophysiological recordingsPreprint
Siebenhühner, F., Wang, S. H., Arnulfo, G., Lampinen, A., Nobili, L., Palva, J. M., & Palva, S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/547638 · Cited by 13 · see citing works
- Authors
- Florin, E., & Baillet, S.
- Affiliations
- Montreal Neurological Institute and Hospital (CA)
- Corresponding author
- Baillet, Sylvain
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 111
- Pages
- 26-35
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4387013
- OpenAlex
- W2025209343
- Cited by
- 184
- References
- 50
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 10 · 2023: 22 · 2022: 19 · 2021: 20 · 2020: 17 · 2019: 19 · 2018: 14 · 2017: 19 · 2016: 13 · 2015: 10
- FWCI
- 11.22
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (DFG: FL 760 2-1)
- Montreal Neurological Institute's National Bank Fellowship
- Agence Nationale pour la Recherche (ANR-BLAN08-0250)
- Killam Foundation
- National Science and Engineering Research Council of Canada
- NIH (2R01EB009048-05)
- 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, cross-frequency coupling, phase-amplitude coupling, neural oscillations, high-frequency oscillations, spontaneous neural fluctuations, magnetoencephalography
- MeSH terms
- Adult, Brain Mapping, Cerebral Cortex, Female, Humans, Male, Nerve Net, Magnetoencephalography, Young Adult
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