Network Communities of Dynamical Influence.

Abstract:

:Fuelled by a desire for greater connectivity, networked systems now pervade our society at an unprecedented level that will affect it in ways we do not yet understand. In contrast, nature has already developed efficient networks that can instigate rapid response and consensus when key elements are stimulated. We present a technique for identifying these key elements by investigating the relationships between a system's most dominant eigenvectors. This approach reveals the most effective vertices for leading a network to rapid consensus when stimulated, as well as the communities that form under their dynamical influence. In applying this technique, the effectiveness of starling flocks was found to be due, in part, to the low outdegree of every bird, where increasing the number of outgoing connections can produce a less responsive flock. A larger outdegree also affects the location of the birds with the most influence, where these influentially connected birds become more centrally located and in a poorer position to observe a predator and, hence, instigate an evasion manoeuvre. Finally, the technique was found to be effective in large voxel-wise brain connectomes where subjects can be identified from their influential communities.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Clark R,Punzo G,Macdonald M

doi

10.1038/s41598-019-53942-4

subject

Has Abstract

pub_date

2019-11-26 00:00:00

pages

17590

issue

1

issn

2045-2322

pii

10.1038/s41598-019-53942-4

journal_volume

9

pub_type

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