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 predict that purely focal and transient perturbations in activity result in diffuse network reorganization affecting distant brain systems.
“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
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.
“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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Self-citationSpecificity and robustness of long-distance connections in weighted, interareal connectomes
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Self-citationDynamics of large-scale electrophysiological networks: A technical review
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Consistency-based thresholding of the human connectome
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From maps to multi-dimensional network mechanisms of mental disorders
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Self-citationOptimal trajectories of brain state transitions
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Local structure-function relationships in human brain networks across the lifespan
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Dynamic interdependence and competition in multilayer networks
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Subcortical contributions to large-scale network communication
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Self-citationTopographic gradients of intrinsic dynamics across neocortex
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Self-citationThe modular organization of human anatomical brain networks: Accounting for the cost of wiring
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“, 2016)—and this is precisely what is observed for “rich club” connectivity cores (Sporns, 2013; Mišić et al., 2015; Cohen and D’Esposito, 2016; Mohr et al., 2016).”
BackgroundMapping how local perturbations influence systems-level brain dynamics
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Structure-function coupling in the human connectome: A machine learning approach
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Learning function from structure in neuromorphic networks
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Self-citationLocal molecular and global connectomic contributions to cross-disorder cortical abnormalities
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Self-citationInformation decomposition and the informational architecture of the brain
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Replay, the default mode network and the cascaded memory systems model
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Self-citationLocal vulnerability and global connectivity jointly shape neurodegenerative disease propagation
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Self-citationDriving the brain towards creativity and intelligence: A network control theory analysis
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Self-citationFrom connectome to cognition: The search for mechanism in human functional brain networks
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Dopamine Signaling Modulates the Stability and Integration of Intrinsic Brain Networks
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Self-citationPatient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy
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A spectrum of routing strategies for brain networks
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Self-citationDiversity of meso-scale architecture in human and non-human connectomes
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Towards a biologically annotated brain connectome
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Self-citationConnectome-based lesion-symptom mapping (CLSM): A novel approach to map neurological function
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Time-resolved structure-function coupling in brain networks
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Self-citationFragility and volatility of structural hubs in the human connectome
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Self-citationEdges in brain networks: Contributions to models of structure and function
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Self-citationData-driven modelling of neurodegenerative disease progression: thinking outside the black box
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Inferring neural signalling directionality from undirected structural connectomes
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Knowledge gaps in the early growth of semantic feature networks
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Weighted Stochastic Block Models of the Human Connectome across the Life Span
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Self-citationNetwork structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia
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Self-citationHub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome
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Dynamic representations in networked neural systems
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Network-Based Asymmetry of the Human Auditory System
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Self-citationModels of Network Spread and Network Degeneration in Brain Disorders
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Spectral graph theory of brain oscillations
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Network Controllability in Transmodal Cortex Predicts Positive Psychosis Spectrum Symptoms
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Structural-functional brain network coupling predicts human cognitive ability
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Self-citationEmerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity
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- 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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