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Multiscale Information Propagation in Emergent Functional Networks
Authors:Arsham Ghavasieh  Manlio De Domenico
Affiliation:1.Department of Physics, University of Trento, Via Sommarive 5, 38123 Povo, Trento , Italy;2.CoMuNe Laboratory, Fondazione Bruno Kessler, Via Sommarive 18, 38123 Povo, Trento, Italy
Abstract:Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for the information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high.
Keywords:information dynamics   multiscale analysis   networks entropy   network density matrix   fungal networks
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