CoBCoM Lectures 2021 - Structural Brain Network Alignment and Similarity
Channel: CoBCoM
Date: 2021-07-08

This video is based on a joint work with the COATI project team at Inria Sophia Antipolis - Méditerranée.


An important part of our current understanding of the structure of the human brain relies on the concept of brain network, which is obtained by looking at how different brain regions are connected with each other. In this work we present a strategy for choosing a suitable parcellation of the brain for structural connectivity studies by making use of the concepts of network alignment and similarity. To do so, we design a novel similarity measure between weighted networks called graph Jaccard index, and a new network alignment technique called WL-align. By assessing the possibility to retrieve graph matchings that provide highly similar graphs, we show that morphology- and structure-based atlases define brain networks that are more topologically robust across a wide range of resolutions.


Matteo Frigo, Emilio Cruciani, David Coudert, Rachid Deriche, Emanuele Natale, Samuel Deslauriers-Gauthier; "Network alignment and similarity reveal atlas-based topological differences in structural connectomes". Network Neuroscience 2021; https://doi.org/10.1162/netn_a_00199


This work was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC Advanced Grant agreement No 694665: CoBCoM - Computational Brain Connectivity Mapping). https://project.inria.fr/cobcom/