Scientific Reports (Sep 2018)

Assortative mixing in spatially-extended networks

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

DOI
https://doi.org/10.1038/s41598-018-32160-4
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 8

Abstract

Read online

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.

Keywords