1. Analysis of Connectome Graphs Based on Boundary Scale
- Author
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Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. TIC171: Diseño de Interfaces Avanzados (Diana), Universidad de Sevilla. TIC245: Topological Pattern Analysis, Recognition and Learning, Universidad de Sevilla. TEP108: Robótica y Tecnología de Computadores, MCIN/AEI/10.13039/501100011033 and Feder Funds project Par-Hot PID2019-110455GB-I00, MCIN/AEI/10.13039/501100011033 and Feder Funds project CIUCAP-HSF US-1381077, Morón Fernández, María José, Amedeo, Ludovica Maria, Monterroso Muñoz, Alberto, Molina Abril, Helena, Díaz del Río, Fernando, Bini, Fabiano, Marinozzi, Franco, Real Jurado, Pedro, Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. TIC171: Diseño de Interfaces Avanzados (Diana), Universidad de Sevilla. TIC245: Topological Pattern Analysis, Recognition and Learning, Universidad de Sevilla. TEP108: Robótica y Tecnología de Computadores, MCIN/AEI/10.13039/501100011033 and Feder Funds project Par-Hot PID2019-110455GB-I00, MCIN/AEI/10.13039/501100011033 and Feder Funds project CIUCAP-HSF US-1381077, Morón Fernández, María José, Amedeo, Ludovica Maria, Monterroso Muñoz, Alberto, Molina Abril, Helena, Díaz del Río, Fernando, Bini, Fabiano, Marinozzi, Franco, and Real Jurado, Pedro
- Abstract
The purpose of this work is to advance in the computational study of connectome graphs from a topological point of view. Specifically, starting from a sequence of hypergraphs associated to a brain graph (obtained using the Boundary Scale model, BS² ), we analyze the resulting scalespace representation using classical topological features, such as Betti numbers and average node and edge degrees. In this way, the topological information that can be extracted from the original graph is substantially enriched, thus providing an insightful description of the graph from a clinical perspective. To assess the qualitative and quantitative topological information gain of the BS² model, we carried out an empirical analysis of neuroimaging data using a dataset that contains the connectomes of 96 healthy subjects, 52 women and 44 men, generated from MRI scans in the Human Connectome Project. The results obtained shed light on the differences between these two classes of subjects in terms of neural connectivity.
- Published
- 2023