A Graphlet-Based Topological Characterization of the Resting-State Network in Healthy People.

ABSTRACT: In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional magnetic resonance imaging (fMRI). Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs. We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node of the atlas "touches" the independent orbits defined by the graphlet set. We focus on the 56 independent columns

SUBMITTER: Finotelli P 

PROVIDER: S-EPMC8113409 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature