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Cooperative and Competitive Spreading Dynamics on the Human Connectome
Open accessAbstract
Increasingly detailed data on the network topology of neural circuits create a need for theoretical principles that explain how these networks shape neural communication. Here we use a model of cascade spreading to reveal architectural features of human brain networks that facilitate spreading. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we investigate scenarios where perturbations initiated at seed nodes result in global cascades that interact either cooperatively or competitively. We find that hub regions and a backbone of pathways facilitate early spreading, while the shortest path structure of the connectome enables cooperative effects, accelerating the spread of cascades. Finally, competing cascades become integrated by converging on polysensory associative areas. These findings show that the organizational principles of brain networks shape global communication and facilitate integrative function.
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“simulation experiments using structure-function models have predicted that even purely focal and transient perturbations in activity should result in diffuse network reorganization that affects distant brain systems (Alstott et al., 2009; Honey and Sporns, 2008; Misic et al., 2015).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Misic et al., 2015
In the citing paper
“Even the best-performing SC-FC models generally account for less than 50% of the variance in FC across the brain in both humans and non-human primates (Grayson et al., 2016; Messe et al., 2014; Misic et al., 2015).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Misic et al., 2015
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Cites
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
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 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-citationThe 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
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388
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
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426
Novel Type of Phase Transition in a System of Self-Driven Particles
Vicsek, T., Czirók, A., Ben‐Jacob, E., Cohen, I., & Shochet, O. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.1226 · Cited by 7,395
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
Threshold models of collective behavior
Granovetter, M. (1978) · American Journal of Sociology · doi:10.1086/226707 · Cited by 6,072
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Yang, Y., Zheng, Y., Zhen, Y., Tang, S., Zheng, H., & Zheng, Z. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.09.499310
Zhao, X., Chen, K., Wang, H., Gao, Y., Ji, X., & Li, Y. (2023) · Cognitive Neurodynamics · doi:10.1007/s11571-023-09941-3
Verma, P., Ranasinghe, K. G., Prasad, J., Cai, C., Xie, X., Lerner, H., Mizuiri, D., Miller, B. L., Rankin, K. P., Vossel, K. A., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2579392/v2
Verma, P., Ranasinghe, K. G., Prasad, J., Cai, C., Xie, X., Lerner, H., Mizuiri, D., Miller, B. L., Rankin, K., Vossel, K. A., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2579392/v1
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Chung, A. W. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-85280-7.00014-2
Verma, P., Ranasinghe, K. G., Prasad, J., Cai, C., Xie, X., Lerner, H., Mizuiri, D., Miller, B. L., Rankin, K. P., Vossel, K. A., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2579392/v3
Zatorre, R. J. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780197558287.002.0004
Zatorre, R. J. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780197558287.003.0010
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Zatorre, R. J. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780197558287.003.0007
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dos Santos, L. R. P. (2023) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.47.2023.tde-11122023-140352
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Vijayan, A. (2023) · International Conference on Algorithms, Computing and Artificial Intelligence (ACAI) · doi:10.1145/3639631.3639664
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Fukushima, M. (2025) · The Brain & Neural Networks · doi:10.3902/jnns.32.108
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Luppi, A. I., Ali, H., Liu, Z.-Q., Milisav, F., Sala, A., Annen, J., Gozzi, A., Bzdok, D., & Mišić, B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.01.691701
Self-citationVerma, P., Ranasinghe, K. G., Prasad, J., Cai, C., Xie, X., Lerner, H., Mizuiri, D., Miller, B., Rankin, K., Vossel, K. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25440916
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Kelemen, S. F., Goñi, J., Pequito, S., & Ashourvan, A. (2026) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2026.1810942 · Cited by 1
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Park, Y., Cha, Y.-H., Kim, H., Kim, Y., Woo, J. H., Lee, J., Cho, H., Mashour, G. A., Xu, T., Lee, U., et al. (2026) · Current Biology · doi:10.1016/j.cub.2026.06.014 · Cited by 1
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Amos, G., Jordi, L., Ahuja, K., Gerber, A., Hütter, G., Vörös, J., Tringides, C. M., & Vasiliauskaitė, V. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.16.738125
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Kong, J., Jia, Y., Wang, Z., Yang, Y., Huang, Z., Zhu, H., & Yin, D. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.122168
Etémé, A. S., Mvogo, A., Nadarajah, S., Fouda, H. P. E., Kofané, T. C., & Tabi, C. B. (2026) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0336997
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Luca, M. D., Demuru, M., Lopez, E. T., Gallo, E., Cafaro, G., Duma, G. M., Depannemaecker, D., Casagrande, G., Quarantelli, M., Granata, C., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.15.757554
Nguessap, E. L. F., Depannemaecker, D., & Ferreira, F. F. (2026) · European Journal of Neuroscience · doi:10.1111/ejn.70713
Metadata
- Authors
- Mišić, B., Betzel, R. F., Nematzadeh, A., Goñi, J., Griffa, A., Hagmann, P., Flammini, A., Ahn, Y.-Y., & Sporns, O.
- Affiliations
- Indiana University Bloomington (US)
- Centre Hospitalier Universitaire Vaudois (CH)
- Corresponding author
- Sporns, Olaf
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 86
- Issue
- 6
- Pages
- 1518-1529
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2155847838
- Cited by
- 342
- References
- 74
- Citations by year
- 2026: 14 · 2025: 17 · 2024: 32 · 2023: 51 · 2022: 37 · 2021: 31 · 2020: 35 · 2019: 25 · 2018: 36 · 2017: 34 · 2016: 24 · 2015: 6
- FWCI
- 20.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Funders
- National Institute on Aging (P30AG010133, P30 AG-10133)
- 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
- human connectome, global cascades, brain network architecture, diffusion spectrum imaging, hub regions, neural communication, network topology
- MeSH terms
- Adult, Brain, Competitive Behavior, Cooperative Behavior, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Neurological, Neural Pathways, Oxygen, Nonlinear Dynamics, Young Adult, Diffusion Tensor Imaging, Connectome
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