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Two classes of functional connectivity in dynamical processes in networks

Voutsa, Venetia and Battaglia, Demian and Bracken, Louise and Brovelli, Andrea and Costescu, Julia and Diaz Munoz, Mario and Fath, Brian. D. and Funk, Andrea and Guirro, Mel and Hein, Thomas and Kerschner, Christian and Kimmich, Christian and Lima, Vinicius and Messe, Arnaud and Parsons, Anthony. J. and Perez, John and Poeppl, Ronald and Prell, Christina and Recinos, Sonia and Shi, Yanhua and Tiwari, Shubham and Turnbull, Laura and Wainwright, John and Waxenecker, Harald and Huett, Marc-Thorsten (2021) 'Two classes of functional connectivity in dynamical processes in networks.', Journal of the Royal Society Interface, 18 (183). p. 20210486.


The relationship of network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of the last years. Understanding this relationship is of relevance to a range of disciplines – from Neuroscience to Geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity) with a (network) representation of the dynamics (functional connectivity). Here, we show that one can distinguish two classes of functional connectivity – one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes – excitations, regular and chaotic oscillators – and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in Geomorphology, Ecology, Systems Biology, Neuroscience and Socio-Ecological Systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution 4.0.
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Full text:(VoR) Version of Record
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Publisher statement:© 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.
Date accepted:13 September 2021
Date deposited:07 October 2021
Date of first online publication:20 October 2021
Date first made open access:07 October 2021

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