Small-World Brain Networks Revisited
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Publication Date
2016-09-21Journal Title
The Neuroscientist
ISSN
1073-8584
Publisher
Sage
Language
English
Type
Article
This Version
VoR
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Bassett, D. S., & Bullmore, E. (2016). Small-World Brain Networks Revisited. The Neuroscientist https://doi.org/10.1177/1073858416667720
Abstract
It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of
high clustering and short path length; and about 10 years since this metric of complex network topology began to be
widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field
of connectomics. Here, we review briefly the foundational concepts of graph theoretical estimation and generation of
small-world networks. We take stock of some of the key developments in the field in the past decade and we consider
in some detail the implications of recent studies using high-resolution tract-tracing methods to map the anatomical
networks of the macaque and the mouse. In doing so, we draw attention to the important methodological distinction
between topological analysis of binary or unweighted graphs, which have provided a popular but simple approach
to brain network analysis in the past, and the topology of weighted graphs, which retain more biologically relevant
information and are more appropriate to the increasingly sophisticated data on brain connectivity emerging from
contemporary tract-tracing and other imaging studies. We conclude by highlighting some possible future trends in the
further development of weighted small-worldness as part of a deeper and broader understanding of the topology and
the functional value of the strong and weak links between areas of mammalian cortex.
Keywords
graph theory, small-world network, network neuroscience, connectomics, small-world propensity
Sponsorship
DSB
acknowledges support from the John D. and Catherine T. MacArthur
Foundation, the Alfred P. Sloan Foundation, the Army Research
Laboratory and the Army Research Office through contract numbers
W911NF-10-2-0022 and W911NF-14-1-0679, the National
Institute of Health (2-R01-DC-009209-11, 1R01HD086888-01,
R01-MH107235, R01-MH107703, and R21-M MH-106799), the
Office of Naval Research, and the National Science Foundation
(BCS-1441502, CAREER PHY-1554488, and BCS-1631550).
Identifiers
External DOI: https://doi.org/10.1177/1073858416667720
This record's URL: https://www.repository.cam.ac.uk/handle/1810/260656
Rights
Attribution-NonCommercial 4.0 International, Attribution-NonCommercial 4.0 International, Attribution-NonCommercial 4.0 International, Attribution-NonCommercial 4.0 International
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