Persistent homology reveals robustness loss in inhaled substance abuse rs-fMRI networks.
PLoS One
; 19(9): e0310165, 2024.
Article
en En
| MEDLINE
| ID: mdl-39283839
ABSTRACT
Analyzing functional brain activity through functional magnetic resonance imaging (fMRI) is commonly done using tools from graph theory for the analysis of the correlation matrices. A drawback of these methods is that the networks must be restricted to values of the weights of the edges within certain thresholds and there is no consensus about the best choice of such thresholds. Topological data analysis (TDA) is a recently-developed tool in algebraic topology which allows us to analyze networks through combinatorial spaces obtained from them, with the advantage that all the possible thresholds can be considered at once. In this paper we applied TDA, in particular persistent homology, to study correlation matrices from rs-fMRI, and through statistical analysis, we detected significant differences between the topological structures of adolescents with inhaled substance abuse disorder (ISAD) and healthy controls. We interpreted the topological differences as indicative of a loss of robustness in the functional brain networks of the ISAD population.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Encéfalo
/
Imagen por Resonancia Magnética
Límite:
Adolescent
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Female
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Humans
/
Male
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2024
Tipo del documento:
Article
País de afiliación:
México
Pais de publicación:
Estados Unidos