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Two classes of functional connectivity in dynamical processes in networks

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VOUTSA Venetia BATTAGLIA Demian BRACKEN Louise J. BROVELLI Andrea COSTESCU Julia DÍAZ MUNOZ Mario FATH Brian D. FUNK Andrea GUIRRO Mel HEIN Thomas KERSCHNER Christian KIMMICH Christian LIMA Vinicius MESSÉ Arnaud PARSONS Anthony J. PEREZ John PÖPPL Ronald PRELL Christina RECINOS Sonia SHI Yanhua TIWARI Shubham TURNBULL Laura WAINWRIGHT John WAXENECKER Harald HÜTT Marc-Thorsten

Rok publikování 2021
Druh Článek v odborném periodiku
Časopis / Zdroj Journal of the Royal Society Interface
Fakulta / Pracoviště MU

Fakulta sociálních studií

www article - open access
Klíčová slova scale-free graphs; modular graphs; random graphs; synchronisation; excitable dynamics; chaotic oscillators
Přiložené soubory
Popis The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent 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, SC) with a (network) representation of the dynamics (functional connectivity, FC). 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.
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