Journal
CHAOS
Volume 24, Issue 1, Pages -Publisher
AIP Publishing
DOI: 10.1063/1.4858457
Keywords
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Categories
Funding
- Sage Center for the Study of the Mind
- Errett Fisher Foundation
- James S. McDonnell Foundation [220020177]
- FET-Proactive project PLEXMATH [317614]
- European Commission
- EPSRC [EP/J001759/1]
- NIGMS [R21GM099493]
- PHS [NS44393]
- U.S. Army Research Office [W911NF-09-0001]
- EPSRC [EP/J001759/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/J001759/1] Funding Source: researchfish
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We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks. (C) 2014 AIP Publishing LLC.
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