Navigation of brain networks

Caio Seguin*, Martijn P. Van Den Heuvel, Andrew Zalesky

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Understanding the mechanisms of neural communication in largescale brain networks remains a major goal in neuroscience. We investigated whether navigation is a parsimonious routing model for connectomics. Navigating a network involves progressing to the next node that is closest in distance to a desired destination. We developed a measure to quantify navigation efficiency and found that connectomes in a range of mammalian species (human, mouse, and macaque) can be successfully navigated with near-optimal efficiency (>80% of optimal efficiency for typical connection densities). Rewiring network topology or repositioning network nodes resulted in 45-60% reductions in navigation performance. We found that the human connectome cannot be progressively randomized or clusterized to result in topologies with substantially improved navigation performance (>5%), suggesting a topological balance between regularity and randomness that is conducive to efficient navigation. Navigation was also found to (i) promote a resource-efficient distribution of the information traffic load, potentially relieving communication bottlenecks, and (ii) explain significant variation in functional connectivity. Unlike commonly studied communication strategies in connectomics, navigation does not mandate assumptions about global knowledge of network topology. We conclude that the topology and geometry of brain networks are conducive to efficient decentralized communication.

Original languageEnglish
Pages (from-to)6297-6302
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume115
Issue number24
Early online date30 May 2018
DOIs
Publication statusPublished - 12 Jun 2018

Funding

ACKNOWLEDGMENTS. We thank Mikail Rubinov for providing connectivity data for the mouse. Human data were provided by the Human Connec-tome Project, WU–Minn Consortium (1U54MH091657; Principal Investigators David Van Essen and Kamil Ugurbil) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research, and by the McDonnell Center for Systems Neuroscience at Washington University. C.S. is funded by a Melbourne Research Scholarship. M.P.v.d.H. was funded by an ALW (Earth and Life Sciences) open (ALWOP.179) and VIDI (452-16-015) grant from the Netherlands Organization for Scientific Research (NWO) and a Fellowship of MQ. A.Z. is supported by the Australian National Health and Medical Research Council (NHMRC) Senior Research Fellowship B (1136649).

FundersFunder number
National Institutes of Health
National Institute of Mental HealthU54MH091657
NIH Blueprint for Neuroscience Research
McDonnell Center for Systems NeuroscienceALWOP.179, 452-16-015
National Health and Medical Research Council1136649
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

    Keywords

    • Complex networks
    • Connectome
    • Network navigation
    • Neural communication

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