Time-resolved resting-state brain networks
Open accessAbstract
Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.
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Previous fMRI studies show global brain signals transition between high and low connectivity strength over time and these fluctuations relate to coordinated network topology patterns.
“recent experiments using functional MRI data have demonstrated that global brain signals transition between states of high and low connectivity strength over time (Zalesky et al., 2014) and that these fluctuations are related to coordinated patterns of network topology (Betzel et al., 2015)”
From The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2016) · cites this paper as Zalesky et al., 2014
A VAR model order of 11 appropriately mimics the expected temporal signature of the BOLD response in 0.72-s TR data.
“In keeping with Zalesky et al. (Zalesky et al., 2014), VAR model order was set at 11, appropriately mimicking the expected temporal signature of the BOLD response in 0.72s TR data.”
From The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2016) · cites this paper as Zalesky et al., 2014
Cites
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319 · see citing works
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256 · see citing works
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190 · see citing works
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820 · see citing works
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
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 · see citing works
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783 · see citing works
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429 · see citing works
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700 · see citing works
The WU-Minn Human Connectome Project: An overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.041 · Cited by 5,651 · see citing works
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253 · see citing works
Friston, K. J., Harrison, L., & Penny, W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00202-7 · Cited by 4,583 · see citing works
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI
Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.042 · Cited by 4,502 · 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
BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics
Xia, M., Wang, J., & He, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068910 · Cited by 4,106 · see citing works
Testing for nonlinearity in time series: the method of surrogate data
Theiler, J. P., Eubank, S., Longtin, A., Galdrikian, B., & Farmer, J. D. (1992) · Physica D Nonlinear Phenomena · doi:10.1016/0167-2789(92)90102-s · Cited by 3,759 · see citing works
Methods to detect, characterize, and remove motion artifact in resting state fMRI
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748 · 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
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284 · see citing works
Tracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992 · see citing works
Toward 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
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962 · see citing works
Bassett, D. S., & Bullmore, E. (2006) · The Neuroscientist · doi:10.1177/1073858406293182 · Cited by 2,600 · see citing works
Efficiency and Cost of Economical Brain Functional Networks
Achard, S., & Bullmore, E. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030017 · Cited by 2,553 · see citing works
Rich-club organization of the human connectome
van den Heuvel, M. P., & Sporns, O. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3539-11.2011 · Cited by 2,354 · see citing works
Neuronal Avalanches in Neocortical Circuits
Beggs, J. M., & Plenz, D. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-35-11167.2003 · Cited by 2,325 · see citing works
Jackson, D. A. (1993) · Ecology · doi:10.2307/1939574 · Cited by 2,282 · see citing works
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn059 · Cited by 2,175 · see citing works
The global signal and observed anticorrelated resting state brain networks
Fox, M. D., Zhang, D., Snyder, A. Z., & Raichle, M. E. (2009) · Journal of Neurophysiology · doi:10.1152/jn.90777.2008 · Cited by 1,877 · see citing works
Time–frequency dynamics of resting-state brain connectivity measured with fMRI
Chang, C., & Glover, G. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.011 · Cited by 1,808 · see citing works
Dynamic reconfiguration of human brain networks during learning
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018985108 · Cited by 1,705 · see citing works
Multi-task connectivity reveals flexible hubs for adaptive task control
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A., & Braver, T. S. (2013) · Nature Neuroscience · doi:10.1038/nn.3470 · Cited by 1,704 · 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
A whole brain fMRI atlas generated via spatially constrained spectral clustering
Craddock, R. C., James, G. A., Holtzheimer, P. E., Hu, X. P., & Mayberg, H. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.21333 · Cited by 1,636 · see citing works
Resting-state fMRI in the human connectome project
Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., Duff, E., Feinberg, D. A., Griffanti, L., Harms, M. P., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.039 · Cited by 1,502 · see citing works
Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461 · see citing works
The Small World of the Cerebral Cortex
Sporns, O., & Zwi, J. D. (2004) · Neuroinformatics · doi:10.1385/ni:2:2:145 · Cited by 1,356 · see citing works
A neuronal model of a global workspace in effortful cognitive tasks
Dehaene, S., Kerszberg, M., & Changeux, J.-P. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.24.14529 · Cited by 1,347 · see citing works
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
Identification and classification of hubs in brain networks
Sporns, O., Honey, C. J., & Kötter, R. (2007) · PLoS ONE · doi:10.1371/journal.pone.0001049 · Cited by 1,165 · see citing works
Modular and hierarchically modular organization of brain networks
Meunier, D., Lambiotte, R., & Bullmore, E. T. (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00200 · Cited by 1,156 · see citing works
Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.063 · Cited by 1,125 · see citing works
The dynamic brain: from spiking neurons to neural masses and cortical fields
Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000092 · Cited by 1,084 · see citing works
Self-citationRevisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer
Edwards, A. M., Phillips, R. A., Watkins, N. W., Freeman, M. P., Murphy, E. J., Afanasyev, V., Buldyrev, S. V., da Luz, M. G. E., Raposo, E. P., Stanley, E., et al. (2007) · Nature · doi:10.1038/nature06199 · Cited by 931 · 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
Hallquist, M. N., Hwang, K., & Luna, B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.116 · Cited by 753 · see citing works
Evidence for hubs in human functional brain networks
Power, J. D., Schlaggar, B. L., Lessov-Schlaggar, C. N., & Petersen, S. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.07.035 · Cited by 716 · see citing works
Hutchison, R. M., Womelsdorf, T., Gati, J. S., Everling, S., & Menon, R. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.22058 · Cited by 715 · see citing works
Temporally-independent functional modes of spontaneous brain activity
Smith, S. M., Miller, K. L., Moeller, S., Xu, J., Auerbach, E. J., Woolrich, M. W., Beckmann, C. F., Jenkinson, M., Andersson, J., Glasser, M. F., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121329109 · Cited by 702 · 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
Liang, X., Zou, Q., He, Y., & Yang, Y. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1214900110 · Cited by 677 · see citing works
Resting-state fMRI confounds and cleanup
Murphy, K., Birn, R. M., & Bandettini, P. A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.001 · Cited by 666 · see citing works
EEG microstate sequences in healthy humans at rest reveal scale-free dynamics.
Van De Ville, D., Britz, J., & Michel, C. M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1007841107 · Cited by 606 · see citing works
Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1204185109 · Cited by 538 · see citing works
Broadband criticality of human brain network synchronization
Kitzbichler, M. G., Smith, M. L., Christensen, S. R., & Bullmore, E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000314 · Cited by 527 · see citing works
Network scaling effects in graph analytic studies of human resting-state fMRI data
Fornito, A. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00022 · Cited by 439 · see citing works
On the use of correlation as a measure of network connectivity
Zalesky, A., Fornito, A., & Bullmore, E. T. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.001 · Cited by 430 · see citing works
Cognitive effort drives workspace configuration of human brain functional networks
Kitzbichler, M. G., Henson, R. N. A., Smith, M. L., Nathan, P. J., & Bullmore, E. T. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.0440-11.2011 · Cited by 427 · see citing works
Non-Stationarity in the “Resting Brain’s” Modular Architecture
Jones, D. T., Vemuri, P., Murphy, M. C., Gunter, J. L., Senjem, M. L., Machulda, M. M., Przybelski, S. A., Gregg, B. E., Kantarci, K., Knopman, D. S., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039731 · Cited by 427 · see citing works
Robust detection of dynamic community structure in networks
Bassett, D. S., Porter, M. A., Wymbs, N. F., Grafton, S. T., Carlson, J. M., & Mucha, P. J. (2013) · Chaos: An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4790830 · Cited by 425 · see citing works
Robust detection of dynamic community structure in networks
Bassett, D. S., Porter, M. A., Wymbs, N. F., Grafton, S. T., Carlson, J. M., & Mucha, P. J. (2013) · Oxford University Research Archive (ORA) (University of Oxford) · Cited by 411 · see citing works
Resting brains never rest: computational insights into potential cognitive architectures
Deco, G., Jirsa, V., & McIntosh, A. R. (2013) · Trends in Neurosciences · doi:10.1016/j.tins.2013.03.001 · Cited by 368 · see citing works
Discovering the Human Connectome
Sporns, O. (2012) · The MIT Press eBooks · doi:10.7551/mitpress/9266.001.0001 · Cited by 362 · see citing works
Periodic changes in fMRI connectivity
Handwerker, D. A., Roopchansingh, V., González-Castillo, J., & Bandettini, P. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.078 · Cited by 360 · see citing works
Association between heart rate variability and fluctuations in resting-state functional connectivity
Chang, C., Metzger, C. D., Glover, G. H., Duyn, J. H., Heinze, H., & Walter, M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.038 · Cited by 353 · see citing works
Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI
Chang, C. E., & Glover, G. H. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.048 · Cited by 292 · see citing works
Biophysical Mechanisms of Multistability in Resting-State Cortical Rhythms
Freyer, F., Roberts, J. A., Becker, R., Robinson, P. A., Ritter, P., & Breakspear, M. J. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.6693-10.2011 · Cited by 289 · see citing works
Kötter, R. (2004) · Neuroinformatics · doi:10.1385/ni:2:2:127 · Cited by 273 · see citing works
Transients, Metastability, and Neuronal Dynamics
Friston, K. J. (1997) · NeuroImage · doi:10.1006/nimg.1997.0259 · Cited by 269 · see citing works
Collective transport of coupled particles
Hennig, D., & Mulhern, C. (2012) · The European Physical Journal B · doi:10.1140/epjb/e2011-20818-1 · Cited by 244 · see citing works
Estimating Properties of Autoregressive Forecasts
Stine, R. A. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478542 · Cited by 202 · see citing works
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
Mechanisms of Zero-Lag Synchronization in Cortical Motifs
Gollo, L. L., Mirasso, C. R., Sporns, O., & Breakspear, M. J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003548 · Cited by 145 · see citing works
Dynamic Properties of Functional Connectivity in the Rodent
Keilholz, S. D., Magnuson, M. E., Pan, W., Willis, M., & Thompson, G. J. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0115 · Cited by 136 · see citing works
Superconductivity and NMR investigations of KTl1.5-doped C60
Kraus, M., Freytag, J., G�rtner, S., Vieth, H., Kr�tschmer, W., & L�ders, K. (1991) · The European Physical Journal B · doi:10.1007/bf01387780 · Cited by 131 · see citing works
Echoes of the Brain within Default Mode, Association, and Heteromodal Cortices
Braga, R. M., Sharp, D. J., Leeson, C., Wise, R. G., & Leech, R. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0570-13.2013 · Cited by 124 · see citing works
"Dynamic" Connectivity in Neural Systems
Breakspear, M. (2004) · Neuroinformatics · doi:10.1385/ni:2:2:205 · Cited by 113 · see citing works
Exponential smoothing weighted correlations
Pozzi, F., Matteo, T. D., & Aste, T. (2012) · The European Physical Journal B · doi:10.1140/epjb/e2012-20697-x · Cited by 108 · see citing works
Breakspear, M. J., Williams, L. M., & Stam, C. J. (2003) · Journal of Computational Neuroscience · doi:10.1023/b:jcns.0000004841.66897.7d · Cited by 107 · see citing works
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Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhx179 · Cited by 3,657 · see citing works
The connectomics of brain disorders
Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734 · see citing works
GRETNA: a graph theoretical network analysis toolbox for imaging connectomics
Wang, J., Wang, X., Xia, M., Liao, X., Evans, A. C., & Yong He, A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00386 · Cited by 1,429 · see citing works
The dynamic functional connectome: State-of-the-art and perspectives
Preti, M. G., Bolton, T. A. W., & Ville, D. V. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.061 · Cited by 1,407 · see citing works
The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery
Calhoun, V. D., Miller, R. L., Pearlson, G. D., & Adalı, T. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.015 · Cited by 1,388 · 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
Shine, J. M., Bissett, P. G., Bell, P. T., Koyejo, O., Balsters, J. H., Gorgolewski, K. J., Moodie, C. A., & Poldrack, R. A. (2016) · Neuron · doi:10.1016/j.neuron.2016.09.018 · Cited by 886 · see citing works
Resting-state functional connectivity in major depressive disorder: A review
Mulders, P. C., van Eijndhoven, P. F., Schene, A. H., Beckmann, C. F., & Tendolkar, I. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.07.014 · Cited by 884 · see citing works
Brain network dynamics are hierarchically organized in time
Vidaurre, D., Smith, S. M., & Woolrich, M. W. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705120114 · Cited by 859 · see citing works
Parkes, L., Fulcher, B., Yücel, M., & Fornito, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.073 · Cited by 783 · see citing works
Emotion and the prefrontal cortex: an integrative review
Dixon, M. L., Thiruchselvam, R., Todd, R., & Christoff, K. (2017) · Psychological Bulletin · doi:10.1037/bul0000096 · Cited by 745 · see citing works
Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?
Hindriks, R., Adhikari, M. H., Murayama, Y., Ganzetti, M., Mantini, D., Logothetis, N. K., & Deco, G. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.055 · Cited by 632 · see citing works
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Lurie, D. J., Kessler, D., Bassett, D. S., Betzel, R. F., Breakspear, M., Kheilholz, S., Kucyi, A., Liégeois, R., Lindquist, M. A., McIntosh, A. R., et al. (2020) · Network Neuroscience · doi:10.1162/netn_a_00116 · Cited by 648 · see citing works
Dixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715766115 · Cited by 595 · see citing works
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Petersen, S. E., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.027 · Cited by 553 · see citing works
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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
Betzel, R. F., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.006 · Cited by 587 · see citing works
Human consciousness is supported by dynamic complex patterns of brain signal coordination
Demertzi, A., Tagliazucchi, E., Dehaene, S., Deco, G., Barttfeld, P., Raimondo, F., Martial, C., Fernández-Espejo, D., Rohaut, B., Voss, H. U., et al. (2019) · Science Advances · doi:10.1126/sciadv.aat7603 · Cited by 513 · see citing works
Effects of aging on functional and structural brain connectivity
Damoiseaux, J. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.077 · Cited by 557 · see citing works
Electroencephalographic Resting-State Networks: Source Localization of Microstates
Custo, A., Ville, D. V. D., Wells, W. M., Tomescu, M. I., Brunet, D., & Michel, C. M. (2017) · Brain Connectivity · doi:10.1089/brain.2016.0476 · Cited by 547 · see citing works
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
Distinct Global Brain Dynamics and Spatiotemporal Organization of the Salience Network
Chen, T., Cai, W., Ryali, S., Supekar, K., & Menon, V. (2016) · PLOS Biology · doi:10.1371/journal.pbio.1002469 · Cited by 480 · see citing works
Small-world human brain networks: Perspectives and challenges
Liao, X., Vasilakos, A. V., & Yong He, A. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.03.018 · Cited by 431 · 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 · see citing works
Making big data open: data sharing in neuroimaging
Poldrack, R. A., & Gorgolewski, K. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3818 · Cited by 412 · see citing works
Cooperative and competitive spreading dynamics on the human connectome
Mišić, B., Betzel, R. F., Nematzadeh, A., Goñi, J., Griffa, A., Hagmann, P., Flammini, A., Ahn, Y.-Y., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.035 · Cited by 342 · see citing works
Cui, Z., & Gong, G. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.001 · Cited by 372 · see citing works
Cabral, J., Kringelbach, M. L., & Deco, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.03.045 · Cited by 353 · see citing works
Using brain imaging to improve spatial targeting of transcranial magnetic stimulation for depression
Cash, R. F. H., Weigand, A., Zalesky, A., Siddiqi, S. H., Downar, J., Fitzgerald, P. B., & Fox, M. D. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.05.033 · Cited by 366 · see citing works
Mathematical framework for large-scale brain network modeling in The Virtual Brain
Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.002 · Cited by 356 · see citing works
Network neuroscience theory of human intelligence
Barbey, A. K. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.10.001 · Cited by 355 · see citing works
Karahanoğlu, F. I., & Ville, D. V. D. (2015) · Nature Communications · doi:10.1038/ncomms8751 · Cited by 320 · see citing works
Du, Y., Fu, Z., & Calhoun, V. D. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00525 · Cited by 326 · see citing works
Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI
Bréchet, L., Brunet, D., Birot, G., Rolf Gruetter, A., Michel, C. M., & Jorge, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.029 · Cited by 333 · see citing works
Zhang, J., Cheng, W., Liu, Z., Zhang, K., Lei, X., Yao, Y., Becker, B., Liu, Y., Kendrick, K. M., Lu, G., et al. (2016) · Brain · doi:10.1093/brain/aww143 · Cited by 332 · see citing works
Resting brain dynamics at different timescales capture distinct aspects of human behavior
Liégeois, R., Li, J., Kong, R., Orbán, C., Ville, D. V. D., Ge, T., Sabuncu, M. R., & Yeo, B. T. T. (2019) · Nature Communications · doi:10.1038/s41467-019-10317-7 · Cited by 289 · see citing works
Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation
Yeo, B. T. T., Tandi, J., & Chee, M. W. L. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.018 · Cited by 265 · see citing works
Roberts, J. A., Gollo, L. L., Abeysuriya, R. G., Roberts, G., Mitchell, P. B., Woolrich, M. W., & Breakspear, M. (2019) · Nature Communications · doi:10.1038/s41467-019-08999-0 · Cited by 264 · see citing works
Ekstrom, A. D., Arnold, A. E. G. F., & Iaria, G. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00803 · Cited by 263 · 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
State and Trait Components of Functional Connectivity: Individual Differences Vary with Mental State
Geerligs, L., Rubinov, M., Cam-CAN, & Henson, R. N. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.1324-15.2015 · Cited by 252 · see citing works
Towards a statistical test for functional connectivity dynamics
Zalesky, A., & Breakspear, M. J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.047 · Cited by 257 · see citing works
Towards a new approach to reveal dynamical organization of the brain using topological data analysis
Saggar, M., Sporns, O., Gonzalez-Castillo, J., Bandettini, P. A., Carlsson, G., Glover, G., & Reiss, A. L. (2018) · Nature Communications · doi:10.1038/s41467-018-03664-4 · Cited by 253 · see citing works
High-amplitude cofluctuations in cortical activity drive functional connectivity
Esfahlani, F. Z., Jo, Y., Faskowitz, J., Byrge, L. A., Kennedy, D. P., Sporns, O., & Betzel, R. F. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005531117 · Cited by 241 · see citing works
Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration
Schultz, D. H., & Cole, M. W. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.0358-16.2016 · Cited by 268 · see citing works
Betzel, R. F., Fukushima, M., He, Y., Zuo, X.-N., & Sporns, O. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.001 · Cited by 249 · see citing works
Wang, P., Kong, R., Kong, X., Liégeois, R., Orbán, C., Deco, G., van den Heuvel, M. P., & Yeo, B. T. T. (2019) · Science Advances · doi:10.1126/sciadv.aat7854 · Cited by 231 · see citing works
Principles of dynamic network reconfiguration across diverse brain states
Shine, J. M., & Poldrack, R. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.010 · Cited by 235 · see citing works
Dixon, M. L., Andrews‐Hanna, J. R., Spreng, R. N., Irving, Z. C., Mills, C., Girn, M., & Kalina Christoff, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.073 · Cited by 228 · see citing works
Multilayer modeling and analysis of human brain networks
Domenico, M. D. (2017) · GigaScience · doi:10.1093/gigascience/gix004 · Cited by 221 · 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
Movie viewing elicits rich and reliable brain state dynamics
van der Meer, J. N., Breakspear, M. J., Chang, L. J., Sonkusare, S., & Cocchi, L. (2020) · Nature Communications · doi:10.1038/s41467-020-18717-w · Cited by 223 · see citing works
Liu, J., Liao, X., Xia, M., & Yong He, A. (2017) · Human Brain Mapping · doi:10.1002/hbm.23890 · Cited by 205 · see citing works
Du, Y., Pearlson, G. D., Yu, Q., He, H., Lin, D., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Wu, L., & Calhoun, V. D. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.11.021 · Cited by 209 · see citing works
Shine, J. M., Koyejo, S., & Poldrack, R. A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1604898113 · Cited by 203 · see citing works
Null models in network neuroscience
Váša, F., & Mišić, B. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00601-9 · Cited by 217 · see citing works
Taghia, J., Cai, W., Ryali, S., Kochalka, J., Nicholas, J., Chen, T., & Menon, V. (2018) · Nature Communications · doi:10.1038/s41467-018-04723-6 · Cited by 198 · see citing works
From maps to multi-dimensional network mechanisms of mental disorders
Braun, U., Schaefer, A., Betzel, R. F., Tost, H., Meyer-Lindenberg, A., & Bassett, D. S. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.007 · Cited by 177 · see citing works
Comparing test-retest reliability of dynamic functional connectivity methods
Choe, A. S., Nebel, M. B., Barber, A. D., Cohen, J. R., Xu, Y., Pekar, J. J., Caffo, B. S., & Lindquist, M. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.005 · Cited by 197 · see citing works
Supekar, K., Cai, W., Krishnadas, R., Palaniyappan, L. K., & Menon, V. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.07.020 · Cited by 197 · see citing works
Estimation of dynamic functional connectivity using multiplication of temporal derivatives
Shine, J. M., Koyejo, O., Bell, P. T., Gorgolewski, K. J., Gilat, M., & Poldrack, R. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.064 · Cited by 166 · see citing works
Multilayer network switching rate predicts brain performance
Pedersen, M., Zalesky, A., Omidvarnia, A., & Jackson, G. D. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814785115 · Cited by 195 · see citing works
Replicability of time-varying connectivity patterns in large resting state fMRI samples
Abrol, A., Damaraju, E., Miller, R. L., Stephen, J. M., Claus, E. D., Mayer, A. R., & Calhoun, V. D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.020 · Cited by 193 · see citing works
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
Miller, R. L., Yaesoubi, M., Turner, J. A., Mathalon, D. H., Preda, A., Pearlson, G. D., Adalı, T., & Calhoun, V. D. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149849 · Cited by 190 · see citing works
Advances in resting state fMRI acquisitions for functional connectomics
Raimondo, L., de Oliveira, I. A. F., Heij, J., Priovoulos, N., Kundu, P., Leoni, R. F., & van der Zwaag, W. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118503 · Cited by 184 · see citing works
A Functional Cartography of Cognitive Systems
Mattar, M. G., Cole, M. W., Thompson‐Schill, S. L., & Bassett, D. S. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004533 · Cited by 172 · see citing works
Shine, J. M., Aburn, M. J., Breakspear, M. J., & Poldrack, R. A. (2018) · eLife · doi:10.7554/elife.31130 · Cited by 175 · see citing works
Nomi, J. S., Farrant, K., Damaraju, E., Rachakonda, S., Calhoun, V. D., & Uddin, L. Q. (2016) · Human Brain Mapping · doi:10.1002/hbm.23135 · Cited by 175 · see citing works
Jie, B., Liu, M., & Shen, D. G. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.03.013 · Cited by 174 · see citing works
Network structure shapes spontaneous functional connectivity dynamics
Shen, K., Hutchison, R. M., Bezgin, G., Everling, S., & McIntosh, A. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4903-14.2015 · Cited by 171 · see citing works
LSD alters dynamic integration and segregation in the human brain
Luppi, A. I., Carhart-Harris, R. L., Roseman, L., Pappas, I., Menon, D. K., & Stamatakis, E. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117653 · Cited by 159 · see citing works
Detection of functional brain network reconfiguration during task-driven cognitive states
Telesford, Q. K., Lynall, M.-E., Vettel, J. M., Miller, M. B., Grafton, S. T., & Bassett, D. S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.078 · Cited by 169 · see citing works
Dynamic graph metrics: Tutorial, toolbox, and tale
Sizemore, A. E., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.081 · Cited by 166 · see citing works
Fu, Z., Caprihan, A., Chen, J., Du, Y., Adair, J. C., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Rosenberg, G. A., & Calhoun, V. D. (2019) · Human Brain Mapping · doi:10.1002/hbm.24591 · Cited by 165 · see citing works
Brain network dynamics in high-functioning individuals with autism
Watanabe, T., & Rees, G. (2017) · Nature Communications · doi:10.1038/ncomms16048 · Cited by 165 · see citing works
A Dynamic Core Network and Global Efficiency in the Resting Human Brain
de Pasquale, F., Penna, S. D., Sporns, O., Romani, G. L., & Corbetta, M. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv185 · Cited by 164 · see citing works
Subcortical contributions to large-scale network communication
Bell, P. T., & Shine, J. M. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.036 · Cited by 163 · see citing works
Tang, E., Giusti, C., Baum, G. L., Gu, S., Pollock, E., Kahn, A. E., Roalf, D. R., Moore, T. M., Ruparel, K., Gur, R. C., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-01254-4 · Cited by 163 · see citing works
Dynamic reorganization of brain functional networks during cognition
Bola, M., & Sabel, B. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.057 · Cited by 160 · see citing works
Lord, L.-D., Stevner, A. B. A., Deco, G., & Kringelbach, M. L. (2017) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2016.0283 · Cited by 157 · see citing works
Tools of the trade: estimating time-varying connectivity patterns from fMRI data
Iraji, A., Faghiri, A., Lewis, N., Fu, Z., Rachakonda, S., & Calhoun, V. D. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa114 · Cited by 152 · see citing works
Positive affect, surprise, and fatigue are correlates of network flexibility
Betzel, R. F., Satterthwaite, T. D., Gold, J. I., & Bassett, D. S. (2017) · Scientific Reports · doi:10.1038/s41598-017-00425-z · Cited by 158 · see citing works
Tang, E., Giusti, C., Baum, G. L., Gu, S., Pollock, E., Kahn, A. E., Roalf, D. R., Moore, T. M., Ruparel, K., Gur, R. C., et al. (2017) · RePEc: Research Papers in Economics · Cited by 174 · see citing works
An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data
Schirner, M., Rothmeier, S., Jirsa, V., McIntosh, A. R., & Ritter, P. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.055 · Cited by 150 · see citing works
Yan, C., Yang, Z., Colcombe, S. J., Zuo, X., & Milham, M. P. (2017) · 中国科学通报:英文版 · doi:10.1016/j.scib.2017.09.015 · Cited by 150 · see citing works
Dysfunctional brain dynamics and their origin in Lewy body dementia
Schumacher, J., Peraza, L. R., Firbank, M., Thomas, A. J., Kaiser, M., Gallagher, P., O'Brien, J. T., Blamire, A. M., & Taylor, J. (2019) · Brain · doi:10.1093/brain/awz069 · Cited by 145 · see citing works
Intrinsic functional connectivity variance and state‐specific under‐connectivity in autism
Chen, H., Nomi, J. S., Uddin, L. Q., Duan, X., & Chen, H. (2017) · Human Brain Mapping · doi:10.1002/hbm.23764 · Cited by 137 · 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
Perry, A., Roberts, G. M. P., Mitchell, P. B., & Breakspear, M. J. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0267-2 · Cited by 146 · see citing works
Endless Fluctuations: Temporal Dynamics of the Amplitude of Low Frequency Fluctuations
Liao, W., Chen, H., Li, J., Ji, G., Wu, G., Long, Z., Xu, Q., Duan, X., Cui, Q., & Biswal, B. B. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2904555 · Cited by 143 · see citing works
Assessing the depth of language processing in patients with disorders of consciousness
Gui, P., Jiang, Y., Zang, D., Qi, Z., Tan, J., Hiromi, T., Jiang, J., Wen, Y., Xu, L., Zhao, J., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0639-1 · Cited by 137 · see citing works
Task-related modulation of functional connectivity variability and its behavioral correlations
Elton, A., & Gao, W. (2015) · Human Brain Mapping · doi:10.1002/hbm.22847 · Cited by 137 · see citing works
Chen, B., Xu, T., Zhou, C., Wang, L., Yang, N., Wang, Z., Dong, H.-M., Yang, Z., Zang, Y., Zuo, X., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0144963 · Cited by 136 · see citing works
Fukushima, M., Betzel, R. F., He, Y., van den Heuvel, M. P., Zuo, X., & Sporns, O. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1539-3 · Cited by 136 · see citing works
Prefrontal connectomics: From anatomy to human imaging
Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01156-6 · Cited by 129 · see citing works
Long, Y., Cao, H., Yan, C., Chen, X., Li, L., Castellanos, F. X., Bai, T., Bo, Q., Chen, G., Chen, N., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102163 · Cited by 131 · see citing works
Chen, X., Lu, B., Li, H., Li, X., Wang, Y., Castellanos, F. X., Cao, L., Chen, N.-X., Chen, W., Cheng, Y., et al. (2022) · Psychoradiology · doi:10.1093/psyrad/kkac005 · Cited by 131 · see citing works
Boehm, I., Geisler, D., King, J. A., Ritschel, F., Seidel, M., Araujo, Y. I. D., Petermann, J., Lohmeier, H., Weiss, J., Walter, M., et al. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00346 · Cited by 128 · see citing works
Modeling and interpreting mesoscale network dynamics
Khambhati, A. N., Sizemore, A. E., Betzel, R. F., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.029 · Cited by 124 · see citing works
- Authors
- Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M.
- Affiliations
- The University of Melbourne (AU)
- The University of Queensland (AU)
- QIMR Berghofer Medical Research Institute (AU)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-06-30
- Volume
- 111
- Issue
- 28
- Pages
- 10341-10346
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4104861
- OpenAlex
- W1996196481
- Cited by
- 753
- References
- 79
- Citations by year
- 2026: 18 · 2025: 57 · 2024: 49 · 2023: 49 · 2022: 58 · 2021: 82 · 2020: 74 · 2019: 74 · 2018: 65 · 2017: 98 · 2016: 64 · 2015: 51 · 2014: 13
- FWCI
- 42.01
- 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)
- Minerva Access (University of Melbourne) (submittedVersion)
- Funders
- National Institutes of Health (5u54mh091657-05)
- National Institute of Mental Health (1U54 MH091657, U54-MH091657)
- 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 Neuroimaging Techniques and Applications
- Keywords
- resting-state brain networks, dynamic functional connectivity, brain network topology, default mode network, frontoparietal network, network hubs, information transmission efficiency, metabolic cost, brain dynamics, Human Connectome Project
- MeSH terms
- Adult, Brain, Humans, Magnetic Resonance Imaging, Male, Mental Processes, Nerve Net, Radiography
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