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Abstract #1601

A Graph-Theory Approach to Study the Effect of Cognitive Load on Resting State Networks

Tommaso Gili1, Paolo Barucca2, Francesco De Santis2, Guido Caldarelli3, Emiliano Macaluso4, Bruno Maraviglia2, Federico Giove2

1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom; 2Dipartimento di Fisica, Universit di Roma Sapienza, Roma, Italy; 3CNR-ISC Dipartimento di Fisica, Universit di Roma Sapienza, Roma, Italy; 4Neuroimaging Laboratory, Santa Lucia Foundation, Roma, Italy

The interaction between different brain structures in the study of functional connectivity is a good conceptual match for considering the brain as a graph, or complex network, of nodes and links. In this representation, image voxels or parcellated brain regions represent the nodes and a measure of similarity in their responses defines the links between them. In this work we focused on a particular type of method that identifies nodes, which play central roles within the network structure. Specifically we calculated Eigenvector Centrality maps of the brain at rest and during a 2-back verbal working memory task.