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Applied Network Science
Fig. 2 | Applied Network Science

Fig. 2

From: Can local-community-paradigm and epitopological learning enhance our understanding of how local brain connectivity is able to process, learn and memorize chronic pain?

Fig. 2

The figure is a visual representation of the LCP-theory proposed to model local-topology-dependent link-growth in complex networks. Let’s focus on a network link between two seed nodes X and Y (black). Nodes that are first-level neighbours of the seed nodes and that are shared between them represent their common neighbours (CN, orange). In green are shown links to first-level neighbours that are not shared. The cohort of the CNs together with their cross-interactions, named local community links (LCL, purple), form a local community. According to the LCP-theory, in many complex networks there is a high positive correlation between the number of CNs and the number of the corresponding LCLs for each link in the network, and both the information should be exploited in order to explain the local-topology-based emergence of links in the network that is named epitopological learning

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