Articles producció científicaEnginyeria Informàtica i Matemàtiques

Percolation in networks with local homeostatic plasticity

  • Datos identificativos

    Identificador:  imarina:9381081
    Autores:  Rapisardi, G; Kryven, I; Arenas, A
    Resumen:
    Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations.
  • Otros:

    Enlace a la fuente original: https://www.nature.com/articles/s41467-021-27736-0
    Referencia de l'ítem segons les normes APA: Rapisardi, G; Kryven, I; Arenas, A (2022). Percolation in networks with local homeostatic plasticity. Nature Communications, 13(1), 122-. DOI: 10.1038/s41467-021-27736-0
    Referencia al articulo segun fuente origial: Nature Communications. 13 (1): 122-
    DOI del artículo: 10.1038/s41467-021-27736-0
    Año de publicación de la revista: 2022-01-10
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2026-05-09
    Autor/es de la URV: Arenas Moreno, Alejandro / Rapisardi, Giacomo
    Departamento: Enginyeria Informàtica i Matemàtiques
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Rapisardi, G; Kryven, I; Arenas, A
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Physics and astronomy (miscellaneous), Physics and astronomy (all), Multidisciplinary sciences, Multidisciplinary, General physics and astronomy, General medicine, General chemistry, General biochemistry,genetics and molecular biology, Ciencias sociales, Ciencias humanas, Chemistry (miscellaneous), Chemistry (all), Biochemistry, genetics and molecular biology (miscellaneous), Biochemistry, genetics and molecular biology (all), Astronomia / física, Antropologia / arqueologia
    Direcció de correo del autor: alexandre.arenas@urv.cat, alexandre.arenas@urv.cat
  • Palabras clave:

    Neural networks
    computer
    Nerve net
    Models
    statistical
    Humans
    Homeostasis
    Computer simulation
    Animals
    Algorithms
    Biochemistry
    Genetics and Molecular Biology (Miscellaneous)
    Chemistry (Miscellaneous)
    Multidisciplinary
    Multidisciplinary Sciences
    Physics and Astronomy (Miscellaneous)
    Physics and astronomy (all)
    General physics and astronomy
    General medicine
    General chemistry
    General biochemistry
    genetics and molecular biology
    Ciencias sociales
    Ciencias humanas
    Chemistry (all)
    genetics and molecular biology (all)
    Astronomia / física
    Antropologia / arqueologia
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