Correspondence:
[*]
Address for correspondence: Department of Computer Science, University of Verona, Verona, Italy
Note: [†] These authors equally contributed to the work
Abstract: Graph-based network modeling is becoming increasingly pervasive touching very different fields. Among these are social networks analysis and brain connectivity modeling. Though apparently very far apart, these two domains share the same questions about how the underlying network is structured and how this can be measured. This determines an a-priori unexpected convergence of the research efforts of two different communities, that is neurosciences and information technology. In this work, we put forth some basic issues emerging from the overlaps of the two domains and propose a first simple measure allowing to capture one among the features of interest: the transtopic closeness centrality. To this end, the related concepts are briefly recalled and two case studies are considered. Then, relying on social network analysis principles, the transposition to functional brain networks is proposed highlighting and discussing some of the inherent critical issues.
