Metastable brain waves

Roberts, James A.; Gollo, Leonardo L.; Abeysuriya, Romesh G.; Roberts, Gloria; Mitchell, Philip B.; Woolrich, Mark W.; Breakspear, Michael

doi:10.1038/s41467-019-08999-0

Cited by 264Neural dynamics and brain functionFunctional Brain Connectivity StudiesNonlinear Dynamics and Pattern Formation

Metastable brain waves

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Roberts, James A., Gollo, Leonardo L., Abeysuriya, Romesh G., Roberts, Gloria, Mitchell, Philip B., Woolrich, Mark W., Breakspear, Michael·2019·Nature Communications

DOI 10.1038/s41467-019-08999-0PMC PMC6401142

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Abstract

Traveling patterns of neuronal activity—brain waves—have been observed across a breadth of neuronal recordings, states of awareness, and species, but their emergence in the human brain lacks a firm understanding. Here we analyze the complex nonlinear dynamics that emerge from modeling large-scale spontaneous neural activity on a whole-brain network derived from human tractography. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. These metastable dynamics accord with empirical data from multiple imaging modalities, including electrical waves in cortical tissue, sequential spatiotemporal patterns in resting-state MEG data, and large-scale waves in human electrocorticography. By moving the study of functional networks from a spatially static to an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena across functional neuroimaging modalities and makes specific predictions for further experimentation.

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Evidence suggests that neural fluctuations involve multiplicative rather than merely additive noise components, where the variance of the noise depends on the system's state.
“Evidence suggests that neural fluctuations involve multiplicative rather than merely additive noise components, where the variance of the noise depends on the system’s state (Buice et al. 2010; Roberts et al. 2019).”
From The myth of the Bayesian brain (2025) · cites this paper as Roberts et al. 2019
The Discussion (page unavailable) says that most analyses omitted noise and that sustained fluctuations arose from chaotic node dynamics. The Methods, “Neural mass model” (page unavailable), describes added Gaussian white noise with a specified standard deviation, but does not say its variance depends on the system’s state. Searches for multiplicative noise and state-dependent noise variance found no passage supporting that distinction. (LLM, conf=0.76)
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Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · see citing works
Functional Network Organization of the Human Brain
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.006 · Cited by 4,124 · see citing works
Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons
Wilson, H. R., & Cowan, J. D. (1972) · Biophysical Journal · doi:10.1016/s0006-3495(72)86068-5 · Cited by 3,579 · see citing works
Predicting human resting-state functional connectivity from structural connectivity
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811168106 · Cited by 3,307 · see citing works
Rhythms for cognition: communication through coherence
Fries, P. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.034 · Cited by 2,725 · see citing works
Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution
Tournier, J., Calamante, F., & Connelly, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.016 · Cited by 2,191 · see citing works
Network structure of cerebral cortex shapes functional connectivity on multiple time scales
Honey, C. J., Kötter, R., Breakspear, M. J., & Sporns, O. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0701519104 · Cited by 1,683 · see citing works
Self-citation
MRtrix: Diffusion tractography in crossing fiber regions
Tournier, J., Calamante, F., & Connelly, A. (2012) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22005 · Cited by 1,370 · see citing works
Dynamic models of large-scale brain activity
Breakspear, M. (2017) · Nature Neuroscience · doi:10.1038/nn.4497 · Cited by 1,239 · see citing works
Self-citation
Whole-brain anatomical networks: does the choice of nodes matter?
Zalesky, A., Fornito, A., Harding, I. H., Cocchi, L., Yücel, M., Pantelis, C., & Bullmore, E. T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.027 · Cited by 1,169 · see citing works
Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics
Friston, K. J., Mechelli, A., Turner, R., & Price, C. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0630 · Cited by 1,131 · see citing works
Stochastic resonance without tuning
Collins, J. J., Chow, C. C., & Imhoff, T. T. (1995) · Nature · doi:10.1038/376236a0 · Cited by 821 · see citing works
High-cost, high-capacity backbone for global brain communication
van den Heuvel, M. P., Kahn, R. S., Goñi, J., & Sporns, O. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1203593109 · Cited by 781 · see citing works
On the nature of seizure dynamics
Jirsa, V., Stacey, W. C., Quilichini, P., Ivanov, A., & Bernard, C. (2014) · Brain · doi:10.1093/brain/awu133 · Cited by 760 · see citing works
Key role of coupling, delay, and noise in resting brain fluctuations
Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kötter, R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901831106 · Cited by 756 · see citing works
Time-resolved resting-state brain networks
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400181111 · Cited by 753 · see citing works
Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors
Deco, G., & Jirsa, V. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.2523-11.2012 · Cited by 680 · see citing works
A mathematical theory of visual hallucination patterns
Ermentrout, G. B., & Cowan, J. D. (1979) · Biological Cybernetics · doi:10.1007/bf00336965 · Cited by 600 · see citing works
Cortical travelling waves: mechanisms and computational principles
Muller, L., Chavane, F., Reynolds, J. H., & B, T. J. S. A. (2018) · Nature reviews. Neuroscience · doi:10.1038/nrn.2018.20 · Cited by 588 · see citing works
Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations
Deco, G., Ponce-Alvarez, A., Mantini, D., Romani, G. L., Hagmann, P., & Corbetta, M. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1091-13.2013 · Cited by 576 · see citing works
Fast transient networks in spontaneous human brain activity
Baker, A. P., Brookes, M. J., Rezek, I. A., Smith, S. M., Behrens, T. E. J., Probert-Smith, P., & Woolrich, M. W. (2014) · eLife · doi:10.7554/elife.01867 · Cited by 555 · see citing works
Self-citation
On the stability of BOLD fMRI correlations
Laumann, T. O., Snyder, A. Z., Mitra, A., Gordon, E. M., Gratton, C., Adeyemo, B., Gilmore, A. W., Nelson, S. M., Berg, J. J., Greene, D. J., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw265 · Cited by 516 · see citing works
Role of local network oscillations in resting-state functional connectivity
Cabral, J., Hugues, E., Sporns, O., & Deco, G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.04.010 · Cited by 515 · see citing works
Generative Models of Cortical Oscillations: Neurobiological Implications of the Kuramoto Model
Breakspear, M. J., Heitmann, S., & Daffertshofer, A. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00190 · Cited by 513 · see citing works
Self-citation
Criticality in the brain: A synthesis of neurobiology, models and cognition
Cocchi, L., Gollo, L. L., Zalesky, A., & Breakspear, M. J. (2017) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2017.07.002 · Cited by 511 · see citing works
Self-citation
Propagating waves mediate information transfer in the motor cortex
Rubino, D., Robbins, K. A., & Hatsopoulos, N. G. (2006) · Nature Neuroscience · doi:10.1038/nn1802 · Cited by 503 · see citing works
Propagation and stability of waves of electrical activity in the cerebral cortex
Robinson, P. A., RENNIE, C. J., & Wright, J. J. (1997) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.56.826 · Cited by 486 · see citing works
A Unifying Explanation of Primary Generalized Seizures Through Nonlinear Brain Modeling and Bifurcation Analysis
Breakspear, M. J., Roberts, J. A., Terry, J. R., Rodrigues, S., Mahant, N., & Robinson, P. A. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhj072 · Cited by 463 · see citing works
Self-citation
Waves, bumps, and patterns in neural field theories
Coombes, S. (2005) · Biological Cybernetics · doi:10.1007/s00422-005-0574-y · Cited by 450 · see citing works
Spatiotemporal dynamics of continuum neural fields
Bressloff, P. C. (2011) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8113/45/3/033001 · Cited by 412 · see citing works
Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders
Deco, G., & Kringelbach, M. L. (2014) · Neuron · doi:10.1016/j.neuron.2014.08.034 · Cited by 402 · see citing works
Spiral Waves in Disinhibited Mammalian Neocortex
Huang, X., Troy, W. C., Yang, Q., Ma, H., Laing, C. R., Schiff, S. J., & Wu, J. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.2705-04.2004 · Cited by 388 · see citing works
Human brain networks function in connectome-specific harmonic waves
Atasoy, S., Donnelly, I., & Pearson, J. (2016) · Nature Communications · doi:10.1038/ncomms10340 · Cited by 381 · cited 1× · see citing works
“The linear treatment of cortical waves under idealized assumptions regarding cortico-cortical connectivity has been well-studied [33, 34], particularly for standing waves [35, 36], as has neuronal wave pattern formation in abstract mathematical settings [26, 37-41].”
Background
Spontaneous cortical activity alternates between motifs defined by regional axonal projections
Mohajerani, M. H., Chan, A. W., Mohsenvand, M. ‘., LeDue, J. M., Liu, R., McVea, D. A., Boyd, J. D., Wang, Y. T., Reimers, M., & Murphy, T. H. (2013) · Nature Neuroscience · doi:10.1038/nn.3499 · Cited by 375 · see citing works
Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks
Vidaurre, D., Hunt, L. T., Quinn, A. J., Hunt, B. A. E., Brookes, M. J., Nobre, A. C., & Woolrich, M. W. (2018) · Nature Communications · doi:10.1038/s41467-018-05316-z · Cited by 362 · see citing works
Self-citation
Transient Cognitive Dynamics, Metastability, and Decision Making
Rabinovich, M. I., Huerta, R., Varona, P., & Afraimovich, V. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000072 · Cited by 349 · see citing works
The dynamics of chimera states in heterogeneous Kuramoto networks
Laing, C. R. (2009) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2009.04.012 · Cited by 325 · see citing works
Visual stimuli induce waves of electrical activity in turtle cortex
Prechtl, J. C., Cohen, L. B., Pesaran, B., Mitra, P. P., & Kleinfeld, D. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.14.7621 · Cited by 321 · see citing works
Change of conduction velocity by regional myelination yields constant latency irrespective of distance between thalamus and cortex
Salami, M., Itami, C., Tsumoto, T., & Kimura, F. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0937380100 · Cited by 314 · see citing works
Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations
Cabral, J., Luckhoo, H., Woolrich, M. W., Joensson, M., Mohseni, H., Baker, A. P., Kringelbach, M. L., & Deco, G. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.047 · Cited by 312 · see citing works
Self-citation
Traveling Waves in Visual Cortex
Sato, T. K., Nauhaus, I., & Carandini, M. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.029 · Cited by 288 · see citing works
Dynamics of travelling waves in visual perception
Wilson, H. R., Blake, R., & Lee, S.-H. (2001) · Nature · doi:10.1038/35091066 · Cited by 287 · see citing works
A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness
Nunez, P. L., & Srinivasan, R. (2006) · Clinical Neurophysiology · doi:10.1016/j.clinph.2006.06.754 · Cited by 281 · see citing works
Reverberation of recent visual experience in spontaneous cortical waves
Han, F., Caporale, N., & Dan, Y. (2008) · Neuron · doi:10.1016/j.neuron.2008.08.026 · Cited by 268 · see citing works
The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave
Muller, L., Reynaud, A., Chavane, F., & Alain Destexhe, A. (2014) · Nature Communications · doi:10.1038/ncomms4675 · Cited by 261 · see citing works
Traveling waves of activity in primary visual cortex during binocular rivalry
Lee, S., Blake, R., & Heeger, D. J. (2004) · Nature Neuroscience · doi:10.1038/nn1365 · Cited by 258 · see citing works
Interpreting temporal fluctuations in resting-state functional connectivity MRI
Liégeois, R., Laumann, T. O., Snyder, A. Z., Zhou, J. H., & Yeo, B. T. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.012 · Cited by 256 · see citing works
Standing waves and traveling waves distinguish two circuits in visual cortex
Benucci, A., Frazor, R. A., & Carandini, M. (2007) · Neuron · doi:10.1016/j.neuron.2007.06.017 · Cited by 254 · see citing works
Propagating Waves of Activity in the Neocortex: What They Are, What They Do
Wu, J., Huang, X., & Zhang, C. (2007) · The Neuroscientist · doi:10.1177/1073858408317066 · Cited by 250 · see citing works
Mirrored Bilateral Slow-Wave Cortical Activity within Local Circuits Revealed by Fast Bihemispheric Voltage-Sensitive Dye Imaging in Anesthetized and Awake Mice
Mohajerani, M. H., McVea, D. A., Fingas, M., & Murphy, T. H. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.6437-09.2010 · Cited by 246 · see citing works
Diameter, Length, Speed, and Conduction Delay of Callosal Axons in Macaque Monkeys and Humans: Comparing Data from Histology and Magnetic Resonance Imaging Diffusion Tractography
Caminiti, R., Carducci, F., Piervincenzi, C., Battaglia‐Mayer, A., Confalone, G., Visco‐Comandini, F., Pantano, P., & Innocenti, G. M. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0761-13.2013 · Cited by 221 · see citing works
The contribution of geometry to the human connectome
Roberts, J. A., Perry, A., Lord, A. R., Roberts, G., Mitchell, P. B., Smith, R. E., Calamante, F., & Breakspear, M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.09.009 · Cited by 213 · see citing works
Self-citation
Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night
Muller, L., Piantoni, G., Koller, D. P., Cash, S. S., Halgren, E., & B, T. J. S. A. (2016) · eLife · doi:10.7554/elife.17267 · Cited by 210 · see citing works
Chaotic itinerancy
Kaneko, K., & Tsuda, I. (2003) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.1607783 · Cited by 209 · see citing works
Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data
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
Self-citation
Consistency-based thresholding of the human connectome
Roberts, J. A., Perry, A., Roberts, G., Mitchell, P. B., & Breakspear, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.053 · Cited by 189 · see citing works
Self-citation
A Canonical Model of Multistability and Scale-Invariance in Biological Systems
Freyer, F., Roberts, J. A., Ritter, P., & Breakspear, M. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002634 · Cited by 186 · see citing works
Self-citation
Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations
Gollo, L. L., Zalesky, A., Hutchison, R. M., van den Heuvel, M. P., & Breakspear, M. J. (2015) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2014.0165 · Cited by 184 · see citing works
Self-citation
Modulation of excitatory synaptic coupling facilitates synchronization and complex dynamics in a biophysical model of neuronal dynamics
Breakspear, M. J., Terry, J. R., & Friston, K. J. (2003) · Network Computation in Neural Systems · doi:10.1088/0954-898x/14/4/305 · Cited by 176 · see citing works
Self-citation
Steady-state visual evoked potentials and travelling waves
Burkitt, G., Silberstein, R. B., Cadusch, P. J., & Wood, A. (2000) · Clinical Neurophysiology · doi:10.1016/s1388-2457(99)00194-7 · Cited by 172 · see citing works
Functional Dysconnection of the Inferior Frontal Gyrus in Young People With Bipolar Disorder or at Genetic High Risk
Roberts, G. M. P., Lord, A., Frankland, A., Wright, A., Lau, P., Lévy, F., Lenroot, R., Mitchell, P. B., & Breakspear, M. J. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.08.018 · Cited by 157 · see citing works
Self-citation
The ictal wavefront is the spatiotemporal source of discharges during spontaneous human seizures
Smith, E. H., Liou, J.-Y., Davis, T. S., Merricks, E. M., Kellis, S., Weiss, S. A., Greger, B. E., House, P. A., McKhann, G. M., Goodman, R. R., et al. (2016) · Nature Communications · doi:10.1038/ncomms11098 · Cited by 155 · see citing works
Mapping how local perturbations influence systems-level brain dynamics
Gollo, L. L., Roberts, J. A., & Cocchi, L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.057 · Cited by 143 · see citing works
Self-citation
A Sensorimotor Role for Traveling Waves in Primate Visual Cortex
Zanos, T. P., Mineault, P., Nasiotis, K., Guitton, D., & Pack, C. C. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.043 · Cited by 134 · see citing works
Eigenmodes of brain activity: Neural field theory predictions and comparison with experiment
Robinson, P. A., Zhao, X., Aquino, K. M., Griffiths, J. D., Sarkar, S., & Mehta-Pandejee, G. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.050 · Cited by 127 · see citing works
Human seizures couple across spatial scales through travelling wave dynamics
Martinet, L.-E., Fiddyment, G. M., Madsen, J. R., Eskandar, E. N., Truccolo, W., Eden, U. T., Cash, S. S., & Kramer, M. (2017) · Nature Communications · doi:10.1038/ncomms14896 · Cited by 127 · see citing works
Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer
Besserve, M., Lowe, S., Logothetis, N. K., Schölkopf, B., & Panzeri, S. (2015) · PLoS Biology · doi:10.1371/journal.pbio.1002257 · Cited by 113 · see citing works
Modulation of excitatory synaptic coupling facilitates synchronization and complex dynamics in a biophysical model of neuronal dynamics
Breakspear, M. J., Terry, J. R., & Friston, K. J. (2003) · Network Computation in Neural Systems · doi:10.1088/0954-898x_14_4_305 · Cited by 107 · see citing works
Self-citation
Will a Large Complex System with Time Delays Be Stable?
Jirsa, V., & Ding, M. (2004) · Physical Review Letters · doi:10.1103/physrevlett.93.070602 · Cited by 106 · see citing works
Predicting functional connectivity from structural connectivity via computational models using MRI: An extensive comparison study
Messé, A., Rudrauf, D., Giron, A., & Marrelec, G. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.001 · Cited by 104 · see citing works
Fragility and volatility of structural hubs in the human connectome
Gollo, L. L., Roberts, J. A., Cropley, V., Biase, M. A. D., Pantelis, C., Zalesky, A., & Breakspear, M. J. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0188-z · Cited by 103 · see citing works
Self-citation
Propagating waves in thalamus, cortex and the thalamocortical system: Experiments and models
Muller, L., & Alain Destexhe, A. (2012) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2012.06.005 · Cited by 101 · see citing works
Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states
Deco, G., Cabral, J., Saenger, V. M., Boly, M., Tagliazucchi, E., Laufs, H., Someren, E. J. W. V., Jobst, B., Stevner, A. B. A., & Kringelbach, M. L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.009 · Cited by 98 · see citing works
A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks
Abeysuriya, R., Hadida, J., Sotiropoulos, S. N., Jbabdi, S., Becker, R., Hunt, B. A. E., Brookes, M. J., & Woolrich, M. W. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006007 · Cited by 96 · see citing works
Self-citation
The frustrated brain: from dynamics on motifs to communities and networks
Gollo, L. L., & Breakspear, M. J. (2014) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0532 · Cited by 92 · see citing works
Self-citation
Waves in Neural Media
Bressloff, P. C. (2013) · Lecture notes on mathematical modelling in the life sciences · doi:10.1007/978-1-4614-8866-8 · Cited by 87 · see citing works
Hemodynamic Traveling Waves in Human Visual Cortex
Aquino, K. M., Schira, M. M., Robinson, P. A., Drysdale, P. M., & Breakspear, M. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002435 · Cited by 84 · see citing works
Self-citation
Interrelating anatomical, effective, and functional brain connectivity using propagators and neural field theory
Robinson, P. A. (2012) · Physical Review E · doi:10.1103/physreve.85.011912 · Cited by 83 · see citing works
Intra-cortical propagation of EEG alpha oscillations
Hindriks, R., van Putten, M. J. A. M., & Deco, G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.08.027 · Cited by 82 · see citing works
Emergence of Complex Wave Patterns in Primate Cerebral Cortex
Townsend, R. G., Solomon, S. S., Chen, S. C., Pietersen, A. N. J., Martin, P. R., Solomon, S. G., & Gong, P. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4509-14.2015 · Cited by 80 · see citing works
Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex
Lu, Y., Truccolo, W., Wagner, F. B., Vargas-Irwin, C. E., Ozden, I., Zimmermann, J. B., May, T., Agha, N. S., Wang, J., & Nurmikko, A. V. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00792.2014 · Cited by 68 · see citing works
Using computational models to relate structural and functional brain connectivity
Hlinka, J., & Coombes, S. (2012) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2012.08081.x · Cited by 60 · see citing works
The organisation of the elderly connectome
Perry, A., Wen, W. X., Lord, A., Thalamuthu, A., Roberts, G. M. P., Mitchell, P. B., Sachdev, P. S., & Breakspear, M. J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.009 · Cited by 59 · see citing works
Self-citation
Large-Scale Cortical Dynamics of Sleep Slow Waves
Botella‐Soler, V., Valderrama, M., Crépon, B., Navarro, V., & Quyen, M. L. V. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030757 · Cited by 42 · see citing works
Deconvolution of neural dynamics from fMRI data using a spatiotemporal hemodynamic response function
Aquino, K. M., Robinson, P. A., Schira, M. M., & Breakspear, M. J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.001 · Cited by 42 · see citing works
Self-citation
Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer
Roberts, J. A., Friston, K. J., & Breakspear, M. J. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.01.010 · Cited by 41 · see citing works
Self-citation
Modeling distributed axonal delays in mean-field brain dynamics
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Self-citation
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Self-citation
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[79]Ester, M., Kriegel, H. -P., Sander, J. & Xu, X. in Proc. Second International Conference on Knowledge Discovery and Data Mining 226–231 (AAAI Press).

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Self-citation
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Self-citation
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Self-citation
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Tang, E., Ju, H., Baum, G. L., Roalf, D. R., Satterthwaite, T. D., Pasqualetti, F., & Bassett, D. S. (2020) · Physical review. E · doi:10.1103/physreve.101.062301 · Cited by 20 · see citing works
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Papo, D., & Buldú, J. M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.029
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Wojtusiak, A., Balanov, A. G., & Savel'ev, S. E. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.110383 · Cited by 17 · see citing works
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Pattern selection by material aging: Modeling chemical gardens in two and three dimensions
Batista, B. C., Morris, A. Z., & Steinbock, O. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2305172120 · Cited by 15 · see citing works
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“Multiplicative noise processes: Evidence suggests that neural fluctuations involve multiplicative rather than merely additive noise components, where the variance of the noise depends on the system’s state (Buice et al. 2010; Roberts et al. 2019).”

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Roberts, J. (2019) · TheScienceBreaker · doi:10.25250/thescbr.brk270
Self-citation
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Meyer‐Lindenberg, A., Ziemann, U., Hajak, G., Cohen, L. G., & Berman, K. F. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.162114799 · Cited by 186 · see citing works
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Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
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The dynamics of resting\nfluctuations in the brain:\nmetastability and its dynamical\ncortical core
Deco, G., Kringelbach, M. L., Jirsa, V., & Ritter, P. (n.d.) · RECERCAT (Consorci de Serveis Universitaris de Catalunya)

Authors: Roberts, J. A., Gollo, L. L., Abeysuriya, R. G., Roberts, G., Mitchell, P. B., Woolrich, M. W., & Breakspear, M.
Affiliations: QIMR Berghofer Medical Research Institute (AU)
University of Oxford (GB)
Black Dog Institute (AU)
Corresponding author: Roberts, James A.
ORCID: Roberts, James A.
Gollo, Leonardo L.
Abeysuriya, Romesh G.
Roberts, Gloria
Mitchell, Philip B.
Woolrich, Mark W.
Breakspear, Michael
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2019-03-05
Volume: 10
Issue: 1
Pages: 1056-1056
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-019-08999-0
PMC: PMC6401142
OpenAlex: W2950869179
Cited by: 264
References: 94
Citations by year: 2026: 32 · 2025: 42 · 2024: 36 · 2023: 41 · 2022: 37 · 2021: 26 · 2020: 30 · 2019: 19 · 2018: 1
FWCI: 16.27
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Nature Communications (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Figshare (submittedVersion, cc-by)
NOVA (University of Newcastle Australia) (submittedVersion, cc-by)
Funders: Wellcome Trust (MR/K005464/1, 106183/Z/14/Z, 203139/Z/16/Z, 106183, 203139, 203139/Z/16)
University of Nottingham
Medical Research Council (203139/Z/16/Z, MR/K005464/1)
Australian Research Council (1118153, 1144936, CE140100007)
National Health and Medical Research Council (1145168, CE140100007, 1144936, 1110975, 1118153, 1037196)
Centre of Excellence for Integrative Brain Function, Australian Research Council (CE140100007)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Physical Sciences › Computer Science › Computer Networks and Communications › Nonlinear Dynamics and Pattern Formation
Keywords: neural oscillations, traveling waves, spiral waves, metastable dynamics, nonlinear dynamics, whole-brain networks, phase flow, nonlinear instability, spontaneous neuronal activity, resting-state MEG, electrocorticography, functional networks
MeSH terms: Electrocorticography, Adolescent, Adult, Brain, Computer Simulation, Female, Humans, Male, Models, Neurological, Nerve Net, Neurons, Nonlinear Dynamics, Young Adult, Diffusion Tensor Imaging, Brain Waves, Healthy Volunteers

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