Abstract
Modelling processes and interactions on complex networks can provide insight into the analysis of networks. Appropriate models should be developed to describe processes under interest. On the other hand, social network processes are various and individuals interact in many social networks with different intensities. Many biological networks, such as brain networks, are only partially understood. We discuss modelling approaches and use a recent brain network study as a basis. In order to model subsystem organisation and cooperation, we use a detailed model of the network topology. Two different network models are used to illustrate the ideas: classical network connectivity and influence spreading models represent connectivity based and spreading processes. The use of the influence spreading model is illustrated with calculations of centrality and betweenness measures for discovering and analysing hubs in brain networks. In this paper, the subsystem detection approach in the brain is not based on commonly applied hierarchical clustering methods but instead on a general community detection method. The proposed method enables discovering subsystems and their cooperation not restricted by hierarchical organisation structure. The two example network models show that modelling decisions can lead to different results at least on detailed levels.
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Kuikka, V. (2020). Subsystem Cooperation in Complex Networks - Case Brain Network. In: Barbosa, H., Gomez-Gardenes, J., Gonçalves, B., Mangioni, G., Menezes, R., Oliveira, M. (eds) Complex Networks XI. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-40943-2_14
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DOI: https://doi.org/10.1007/978-3-030-40943-2_14
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