Modular Brain Networks

Sporns, Olaf; Betzel, Richard F.

doi:10.1146/annurev-psych-122414-033634

Cited by 1,334Functional Brain Connectivity StudiesComplex Network Analysis TechniquesAdvanced Neuroimaging Techniques and Applications

The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.

Modular Brain Networks

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Sporns, Olaf, Betzel, Richard F.·2016·Annual Review of Psychology

DOI 10.1146/annurev-psych-122414-033634PMC PMC4782188

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Abstract

The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools. Methods for detecting modules, or network communities, are of particular interest because they uncover major building blocks or subnetworks that are particularly densely connected, often corresponding to specialized functional components. A large number of methods for community detection have become available and are now widely applied in network neuroscience. This article first surveys a number of these methods, with an emphasis on their advantages and shortcomings; then it summarizes major findings on the existence of modules in both structural and functional brain networks and briefly considers their potential functional roles in brain evolution, wiring minimization, and the emergence of functional specialization and complex dynamics.

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Structural connectivity can be partitioned into modules (communities) that reflect clusters embedded in the brain's wiring.
“At the mesocale, structural connectivity can be partitioned into modules (also known as communities) that reflect the presence of clusters embedded in the brain’s wiring (Betzel, 2020; Sporns and Betzel, 2016).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Sporns and Betzel, 2016
When neural networks are hierarchically segregated into distributed neighbourhoods, the range of parameters supporting self-organised criticality widens, permitting subcritical and supercritical dynamics to occur together.
“The hierarchical segregation of neural networks into distributed neighbourhoods has been found to stretch the parameter range for self-organised criticality by allowing subcritical and supercritical dynamics to co-exist simultaneously [75].”
From The depressed brain: an evolutionary systems theory (2017) · cites this paper as [75]

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The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
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
Self-citation
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
Self-citation
Community detection in graphs
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
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
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
The Modularity of Mind
Fodor, J. A. (1983) · doi:10.7551/mitpress/4737.001.0001 · Cited by 7,734
Finding community structure in very large networks
Clauset, A., Newman, M. E. J., & Moore, C. (2004) · Physical Review E · doi:10.1103/physreve.70.066111 · Cited by 7,390
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
The structure of the nervous system of the nematode Caenorhabditis elegans
White, J. G., Southgate, E., Thomson, J. N., & Brenner, S. (1986) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1986.0056 · Cited by 5,589 · cited 2×
“Since its reconstruction in the early 1980s (White et al. 1986), this network has been the subject of many graph-theoretical analyses (Varshney et al. 2011), including several that have attempted to elucidate its division into communities.”
BackgroundMethod
Fast algorithm for detecting community structure in networks
Newman, M. E. J. (2004) · Physical Review E · doi:10.1103/physreve.69.066133 · Cited by 5,415
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005) · Nature · doi:10.1038/nature03607 · Cited by 5,373
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
Maps of random walks on complex networks reveal community structure
Rosvall, M., & Bergstrom, C. T. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706851105 · Cited by 4,583
The Architecture of Complexity
Simon, H. A. (1991) · Springer eBooks · doi:10.1007/978-1-4899-0718-9_31 · Cited by 4,479
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
Self-citation
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
Functional cartography of complex metabolic networks
Guimerà, R., & Nunes Amaral, L. A. (2005) · Nature · doi:10.1038/nature03288 · Cited by 3,983
Preface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,483
Functional and Effective Connectivity: A Review
Friston, K. J. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0008 · Cited by 3,415
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284
Self-citation
The Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260
Self-citation
Benchmark graphs for testing community detection algorithms
Lancichinetti, A., Fortunato, S., & Radicchi, F. (2008) · Physical Review E · doi:10.1103/physreve.78.046110 · Cited by 3,058
Resolution limit in community detection
Fortunato, S., & Barthélemy, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605965104 · Cited by 3,024
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
Self-citation
Comparing community structure identification
Danon, L., Dı́az-Guilera, A., Duch, J., & Arenas, À. (2005) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/2005/09/p09008 · Cited by 2,905
A mesoscale connectome of the mouse brain
Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., Wang, Q., Lau, C., Kuan, L., Henry, A. M., et al. (2014) · Nature · doi:10.1038/nature13186 · Cited by 2,612
Models and Methods in Social Network Analysis
Wasserman, S. S., Scott, J. P., Carrington, P. J., Marsden, P. V., Frank, O., Everett, M. G., Borgatti, S. P., Doreian, P., Batagelj, V., Ferligoj, A., et al. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511811395 · Cited by 2,452
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
Self-citation
Large-scale brain networks in cognition: emerging methods and principles
Bressler, S. L., & Menon, V. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.04.004 · Cited by 2,348
Computing Communities in Large Networks Using Random Walks
Pons, P., & Matthieu Latapy, B. (2005) · Lecture notes in computer science · doi:10.1007/11569596_31 · Cited by 2,217
The modularity of mind: An essay on faculty psychology. By Jerry A. Fodor. Cambridge, MA: MIT Press, 1983. Pp. ix, 145. Cloth $17.50, paper $8.50.
Matthei, E. H. (1984) · Language · doi:10.2307/413815 · Cited by 2,189
Community detection algorithms: A comparative analysis
Lancichinetti, A., & Fortunato, S. (2009) · Physical Review E · doi:10.1103/physreve.80.056117 · Cited by 2,181
Community Structure in Time-Dependent, Multiscale, and Multiplex Networks
Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010) · Science · doi:10.1126/science.1184819 · Cited by 2,123
Structural and Functional Brain Networks: From Connections to Cognition
Park, H.-J., & Friston, K. (2013) · Science · doi:10.1126/science.1238411 · Cited by 2,106
Organization, development and function of complex brain networks
SPORNS, O., CHIALVO, D., KAISER, M., & HILGETAG, C. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.07.008 · Cited by 2,055
Self-citation
Statistical mechanics of community detection
Reichardt, J., & Bornholdt, S. (2006) · Physical Review E · doi:10.1103/physreve.74.016110 · Cited by 2,048
Link communities reveal multiscale complexity in networks
Ahn, Y., Bagrow, J. P., & Lehmann, S. (2010) · Nature · doi:10.1038/nature09182 · Cited by 1,977
Network modelling methods for FMRI
Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., Ramsey, J. D., & Woolrich, M. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.063 · Cited by 1,878
Networks of the Brain: Quantitative Analysis and Modeling
Sporns, O. (2010) · The MIT Press eBooks · doi:10.7551/mitpress/8476.001.0001 · Cited by 1,750
Self-citation
The connectomics of brain disorders
Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734
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
Intrinsic and task-evoked network architectures of the human brain
Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.014 · Cited by 1,564
Community detection in complex networks using extremal optimization
Duch, J., & Arenas, À. (2005) · Physical Review E · doi:10.1103/physreve.72.027104 · Cited by 1,550
Whole-brain functional imaging at cellular resolution using light-sheet microscopy
Ahrens, M. B., Orger, M. B., Robson, D. N., Li, J. M., & Keller, P. J. (2013) · Nature Methods · doi:10.1038/nmeth.2434 · Cited by 1,392
Finding Statistically Significant Communities in Networks
Lancichinetti, A., Radicchi, F., Ramasco, J. J., & Fortunato, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018961 · Cited by 1,200
Evolvability
Kirschner, M., & Gerhart, J. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.15.8420 · Cited by 1,129
Community Structure in Directed Networks
Leicht, E. A., & Newman, M. E. J. (2008) · Physical Review Letters · doi:10.1103/physrevlett.100.118703 · Cited by 1,118
Performance of modularity maximization in practical contexts
Good, B. H., de Montjoye, Y.-A., & Clauset, A. (2010) · Physical Review E · doi:10.1103/physreve.81.046106 · Cited by 937
Decreased segregation of brain systems across the healthy adult lifespan
Chan, M. Y., Park, D. C., Savalia, N. K., Petersen, S. E., & Wig, G. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415122111 · Cited by 919
Functional system and areal organization of a highly sampled individual human brain
Laumann, T. O., Gordon, E. M., Adeyemo, B., Snyder, A. Z., Joo, S. J., Chen, M.-Y., Gilmore, A. W., McDermott, K. B., Nelson, S. M., Dosenbach, N. U. F., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.037 · Cited by 911
Consensus clustering in complex networks
Lancichinetti, A., & Fortunato, S. (2012) · Scientific Reports · doi:10.1038/srep00336 · Cited by 905
Weight-conserving characterization of complex functional brain networks
Rubinov, M., & Sporns, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.069 · Cited by 903
Self-citation
Spontaneous evolution of modularity and network motifs
Kashtan, N., & Alon, U. S. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0503610102 · Cited by 885
The map equation
Rosvall, M., Axelsson, D., & Bergstrom, C. T. (2009) · The European Physical Journal Special Topics · doi:10.1140/epjst/e2010-01179-1 · Cited by 871
Structural Properties of the Caenorhabditis elegans Neuronal Network
Varshney, L. R., Chen, B. L., Paniagua, E., Hall, D. H., & Chklovskii, D. B. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001066 · Cited by 867
A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex
Markov, N. T., Ercsey-Ravasz, M. M., Ribeiro Gomes, A. R., Lamy, C., Magrou, L., Vezoli, J., Misery, P., Falchier, A., Quilodran, R., Gariel, M. A., et al. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs270 · Cited by 857
Synchronization Reveals Topological Scales in Complex Networks
Arenas, À., Dı́az-Guilera, A., & Vicente, C. J. P. (2006) · Physical Review Letters · doi:10.1103/physrevlett.96.114102 · Cited by 849
Changes in structural and functional connectivity among resting-state networks across the human lifespan
Betzel, R. F., Byrge, L., He, Y., Goñi, J., Zuo, X.-N., & Sporns, O. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.067 · Cited by 807
Self-citation
A Brain-Wide Study of Age-Related Changes in Functional Connectivity
Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M., & Lorist, M. M. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu012 · Cited by 788
Contributions and challenges for network models in cognitive neuroscience
Sporns, O. (2014) · Nature Neuroscience · doi:10.1038/nn.3690 · Cited by 767
Self-citation
Age-related changes in modular organization of human brain functional networks
Meunier, D., Achard, S., Morcom, A., & Bullmore, E. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.062 · Cited by 756
Theoretical Neuroanatomy: Relating Anatomical and Functional Connectivity in Graphs and Cortical Connection Matrices
Sporns, O. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.2.127 · Cited by 712
Self-citation
Hierarchical modularity in human brain functional networks
David Meunier, A. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.037.2009 · Cited by 689
Wiring optimization can relate neuronal structure and function
Chen, B. L., Hall, D. H., & Chklovskii, D. B. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506806103 · Cited by 650
The evolutionary origins of modularity
Clune, J., Mouret, J.-B., & Lipson, H. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2012.2863 · Cited by 631
Line graphs, link partitions, and overlapping communities
Evans, T., & Lambiotte, R. (2009) · Physical Review E · doi:10.1103/physreve.80.016105 · Cited by 621
Learning-induced autonomy of sensorimotor systems
Bassett, D. S., Yang, M., Wymbs, N. F., & Grafton, S. T. (2015) · Nature Neuroscience · doi:10.1038/nn.3993 · Cited by 603
Analysis of connectivity in the cat cerebral cortex
Scannell, J. W., Blakemore, C. B., & Mp, Y. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-02-01463.1995 · Cited by 554
Analysis of the structure of complex networks at different resolution levels
Arenas, À., Fernández, A., & Gómez, S. (2008) · New Journal of Physics · doi:10.1088/1367-2630/10/5/053039 · Cited by 550
Anatomical connectivity defines the organization of clusters of cortical areas in the macaque and the cat
Hilgetag, C. C., Burns, G., O’Neill, M. A., Scannell, J. W., & Young, M. P. (2000) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2000.0551 · Cited by 548
Uncovering cryptic genetic variation
Gibson, G., & Dworkin, I. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1426 · Cited by 546 · cited 1×
“In genetics, such external fluctuations could relate to the effects of cryptic genetic variation, which uncovers novel phenotypes under conditions of environmental change (Gibson & Dworkin 2004), thus potentially promoting increased robustness.”
Background
Limits of modularity maximization in community detection
Lancichinetti, A., & Fortunato, S. (2011) · Physical Review E · doi:10.1103/physreve.84.066122 · Cited by 495
The Connectome of a Decision-Making Neural Network
Jarrell, T. A., Wang, Y., Bloniarz, A. E., Brittin, C. A., Xu, M., Thomson, J. N., Albertson, D. G., Hall, D. H., & Emmons, S. W. (2012) · Science · doi:10.1126/science.1221762 · Cited by 474
Stability of graph communities across time scales
Delvenne, J., Yaliraki, S. N., & Barahona, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903215107 · Cited by 474
Cognitive relevance of the community structure of the human brain functional coactivation network
Crossley, N. A., Mechelli, A., Vértes, P. E., Winton‐Brown, T., Patel, A. X., Ginestet, C. E., McGuire, P. K., & Bullmore, E. T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1220826110 · Cited by 457
Finding communities in linear time: a physics approach
Wu, F., & Huberman, B. A. (2004) · The European Physical Journal B · doi:10.1140/epjb/e2004-00125-x · Cited by 451
The human connectome: Origins and challenges
Sporns, O. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.023 · Cited by 449
Self-citation
Comparing Community Structure to Characteristics in Online Collegiate Social Networks
Red, V., Kelsic, E. D., Mucha, P. J., & Porter, M. A. (2011) · SIAM Review · doi:10.1137/080734315 · Cited by 443
Community detection in networks with positive and negative links
Traag, V., & Bruggeman, J. (2009) · Physical Review E · doi:10.1103/physreve.80.036115 · Cited by 435
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
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
Network Analysis of Corticocortical Connections Reveals Ventral and Dorsal Processing Streams in Mouse Visual Cortex
Wang, Q., Sporns, O., & Burkhalter, A. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.6063-11.2012 · Cited by 410
Self-citation
An anatomical substrate for integration among functional networks in human cortex
van den Heuvel, M. P., & Sporns, O. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2128-13.2013 · Cited by 404
Self-citation
Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits
Bassett, D. S., Greenfield, D. L., Meyer‐Lindenberg, A., Weinberger, D. R., Moore, S. W., & Bullmore, E. T. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000748 · Cited by 401
Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac).
Stephan, K. E., Kamper, L., Bozkurt, A., Burns, G. A., Young, M. P., & Kötter, R. (2001) · Philosophical transactions of the Royal Society of London. Series B, Biological sciences · doi:10.1098/rstb.2001.0908 · Cited by 394
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks
Gallos, L. K., Makse, H. A., & Sigman, M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1106612109 · Cited by 387
BrainMap
Laird, A., Lancaster, J., & Fox, P. (2007) · Neuroinformatics · doi:10.1385/ni:3:1:065 · Cited by 379
Robustness of community structure in networks
Karrer, B., Levina, E., & Newman, M. E. J. (2008) · Physical Review E · doi:10.1103/physreve.77.046119 · Cited by 350
The Rich Club of the C. elegans Neuronal Connectome
Towlson, E. K., Vértes, P. E., Ahnert, S. E., Schafer, W. R., & Bullmore, E. T. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.3784-12.2013 · Cited by 343
Multi-level bootstrap analysis of stable clusters in resting-state fMRI
Bellec, P., Rosa‐Neto, P., Lyttelton, O. C., Benali, H., & Evans, A. C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.082 · Cited by 343
Uncovering space-independent communities in spatial networks
Expert, P., Evans, T., Blondel, V. D., & Lambiotte, R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018962108 · Cited by 342
Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks
Zamora‐López, G. (2010) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.001.2010 · Cited by 333
Rich Club Organization of Macaque Cerebral Cortex and Its Role in Network Communication
Harriger, L., van den Heuvel, M. P., & Sporns, O. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046497 · Cited by 309
Self-citation
Network science
Börner, K., Sanyal, S., & Vespignani, A. (2007) · Annual Review of Information Science and Technology · doi:10.1002/aris.2007.1440410119 · Cited by 296
Varying environments can speed up evolution
Kashtan, N., Noor, Ε., & Alon, U. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0611630104 · Cited by 292
Network architecture of the long-distance pathways in the macaque brain
Modha, D. S., & Singh, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1008054107 · Cited by 283
Multivariate Statistical Analyses for Neuroimaging Data
McIntosh, A. R., & Mišić, B. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-113011-143804 · Cited by 274
Handbook of Brain Connectivity
Jirsa, V., & McIntosh, A. R. (2007) · Understanding complex systems · doi:10.1007/978-3-540-71512-2 · Cited by 273
Online Retrieval, Processing, and Visualization of Primate Connectivity Data From the CoCoMac Database
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Self-citation
Analysis of community structure in networks of correlated data
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Multiresolution community detection for megascale networks by information-based replica correlations
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Detecting complex network modularity by dynamical clustering
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Architecture of the cerebral cortical association connectome underlying cognition
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Self-citation
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Self-citation
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Finding instabilities in the community structure of complex networks
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Self-citation
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Phase transition in the economically modeled growth of a cellular nervous system
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Stochastic Blockmodeling of the Modules and Core of the Caenorhabditis elegans Connectome
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Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations
Lohse, C., Bassett, D. S., Lim, K. O., & Carlson, J. M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003712 · Cited by 62
Modularity produces small-world networks with dynamical time-scale separation
Pan, R. K., & Sinha, S. (2009) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/85/68006 · Cited by 61
The strength of weak connections in the macaque cortico-cortical network
Goulas, A., Schaefer, A., & Margulies, D. S. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0836-3 · Cited by 61
Using Geometry to Uncover Relationships Between Isotropy, Homogeneity, and Modularity in Cortical Connectivity
Henderson, J. A., & Robinson, P. A. (2013) · Brain Connectivity · doi:10.1089/brain.2013.0151 · Cited by 43
Global features of functional brain networks change with contextual disorder
Andric, M., & Hasson, U. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.025 · Cited by 29
Mathematical modeling for evolution of heterogeneous modules in the brain
Yamaguti, Y., & Tsuda, I. (2014) · Neural Networks · doi:10.1016/j.neunet.2014.07.013 · Cited by 26
Probabilistic Clustering of the Human Connectome Identifies Communities and Hubs
Hinne, M., Ekman, M., Janssen, R. J., Heskes, T., & van Gerven, M. A. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117179 · Cited by 25
Community detection in temporal multilayer networks, with an application to correlation networks
Bazzi, M., Porter, M. A., Williams, S., McDonald, M., Fenn, D. J., & Howison, S. D. (2015) · arXiv · doi:10.48550/arxiv.1501.00040

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MacMahon M, 2015, Phys. Rev. X, 5, 021006 [physics
Simon HA, 1962, Proc. Am. Philos. Soc., 106, 467
Zamora-Lopez G, 2010, Front. Neuroinform., 4, 1

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Self-citation
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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 188
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Chan, M. Y., Na, J., Agres, P. F., Savalia, N. K., Park, D. C., & Wig, G. S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714021115 · Cited by 166
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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 165
Multilayer Brain Networks
Vaiana, M., & Muldoon, S. F. (2018) · Journal of Nonlinear Science · doi:10.1007/s00332-017-9436-8 · Cited by 160
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Yu, M., Gouw, A. A., Hillebrand, A., Tijms, B. M., Stam, C. J., van Straaten, E. C. W., & Pijnenburg, Y. A. L. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.03.018 · Cited by 153
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Karuza, E. A., Thompson‐Schill, S. L., & Bassett, D. S. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.06.003 · Cited by 160
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Perry, A., Roberts, G. M. P., Mitchell, P. B., & Breakspear, M. J. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0267-2 · Cited by 152
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Jiang, X., Shen, Y., Yao, J., Zhang, L., Xu, L., Feng, R., Cai, L., Liu, J., Chen, W., & Wang, J. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0467-9 · Cited by 120
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Arnulfo, G., Wang, S. H., Myrov, V. O., Toselli, B., Hirvonen, J., Fato, M., Nobili, L., Cardinale, F., Rubino, A., Zhigalov, A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18975-8 · Cited by 124
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Gallen, C. L., Baniqued, P. L., Chapman, S. B., Aslan, S., Keebler, M. W., Didehbani, N., & D’Esposito, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0169015 · Cited by 122

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Puxeddu, M. G. (2020) · IRIS Research product catalog (Sapienza University of Rome)
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Authors: Sporns, O., & Betzel, R. F.
Affiliations: Indiana University Bloomington (US)
ORCID: Sporns, Olaf
Betzel, Richard F.
Venue: Annual Review of Psychology
Publisher: Annual Reviews
Published: 2016-01-04
Volume: 67
Issue: 1
Pages: 613-640
ISSN: 0066-4308 (ISSN-L)
1545-2085
DOI: 10.1146/annurev-psych-122414-033634
PMC: PMC4782188
OpenAlex: W2143502460
Cited by: 1,334
References: 142
Citations by year: 2026: 102 · 2025: 147 · 2024: 138 · 2023: 133 · 2022: 137 · 2021: 145 · 2020: 135 · 2019: 113 · 2018: 129 · 2017: 93 · 2016: 53
FWCI: 9.31
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Annual Review of Psychology (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Science Foundation (0903495)
James S. McDonnell Foundation (#22002082)
National Institutes of Health
Division of Graduate Education
National Center for Complementary and Integrative Health (R01AT009036)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: brain networks, network modules, community detection, structural connectivity, functional connectivity, graph theory, network neuroscience, brain evolution, functional specialization, complex dynamics
MeSH terms: Brain, Brain Mapping, Humans, Nerve Net

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