Assortative mixing in spatially-extended networks View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-09-14

AUTHORS

Vladimir V. Makarov, Daniil V. Kirsanov, Nikita S. Frolov, Vladimir A. Maksimenko, Xuelong Li, Zhen Wang, Alexander E. Hramov, Stefano Boccaletti

ABSTRACT

We focus on spatially-extended networks during their transition from short-range connectivities to a scale-free structure expressed by heavy-tailed degree-distribution. In particular, a model is introduced for the generation of such graphs, which combines spatial growth and preferential attachment. In this model the transition to heterogeneous structures is always accompanied by a change in the graph's degree-degree correlation properties: while high assortativity levels characterize the dominance of short distance couplings, long-range connectivity structures are associated with small amounts of disassortativity. Our results allow to infer that a disassortative mixing is essential for establishing long-range links. We discuss also how our findings are consistent with recent experimental studies of 2-dimensional neuronal cultures. More... »

PAGES

13825

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-32160-4

DOI

http://dx.doi.org/10.1038/s41598-018-32160-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106921310

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30218078


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