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Methods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists

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dc.contributor.authorPrettejohn, B.
dc.contributor.authorBerryman, M.
dc.contributor.authorMcDonnell, M.
dc.date.issued2011
dc.description.abstractMany simulations of networks in computational neuroscience assume completely homogenous random networks of the Erdös-Rényi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the "scale-free" and "small-world" properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length, and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks.
dc.identifier.citationFrontiers in Computational Neuroscience, 2011; 5(MARCH):1-18
dc.identifier.doi10.3389/fncom.2011.00011
dc.identifier.issn1662-5188
dc.identifier.issn1662-5188
dc.identifier.orcidMcDonnell, M. [0000-0002-7009-3869]
dc.identifier.urihttps://hdl.handle.net/1959.8/119002
dc.language.isoen
dc.publisherFRONTIERS RES FOUND
dc.relation.granthttp://purl.org/au-research/grants/arc/DP1093425
dc.rightsCopyright 2011 Prettejohn, Berryman, McDonnell and Frontiers Media SA
dc.source.urihttps://doi.org/10.3389/fncom.2011.00011
dc.subjectbrain networks
dc.subjectcomplex networks
dc.subjectcortical networks
dc.subjectdirected network
dc.subjectnetwork simulation
dc.subjectscale-free network
dc.subjectsmall-world network
dc.titleMethods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists
dc.typeJournal article
pubs.publication-statusPublished
ror.mmsid9915909358401831

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