Articles producció científicaEnginyeria Informàtica i Matemàtiques

Percolation in networks with local homeostatic plasticity

  • Datos identificativos

    Identificador:  imarina:9381081
    Autores:  Rapisardi, Giacomo; Kryven, Ivan; Arenas, Alex
    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:

    Autor según el artículo: Rapisardi, Giacomo; Kryven, Ivan; Arenas, Alex
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Arenas Moreno, Alejandro / Rapisardi, Giacomo
    Palabras clave: Algorithms; Animals; Computer simulation; Homeostasis; Humans; Models, statistical; Nerve net; Neural networks, computer
    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.
    Áreas temáticas: Antropologia / arqueologia; Astronomia / física; Biochemistry, genetics and molecular biology (all); Biochemistry, genetics and molecular biology (miscellaneous); Biodiversidade; Biotecnología; Chemistry (all); Chemistry (miscellaneous); Ciência da computação; Ciências agrárias i; Ciências ambientais; Ciências biológicas i; Ciências biológicas ii; Ciências biológicas iii; Educação física; Engenharias iv; Farmacia; General biochemistry,genetics and molecular biology; General chemistry; General medicine; General physics and astronomy; Geociências; Interdisciplinar; Matemática / probabilidade e estatística; Materiais; Medicina i; Medicina ii; Medicina iii; Medicina veterinaria; Multidisciplinary; Multidisciplinary sciences; Nutrição; Odontología; Physics and astronomy (all); Physics and astronomy (miscellaneous); Planejamento urbano e regional / demografia; Psicología; Química; Saúde coletiva; Zootecnia / recursos pesqueiros
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: alexandre.arenas@urv.cat
    Fecha de alta del registro: 2024-09-28
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.nature.com/articles/s41467-021-27736-0
    Referencia al articulo segun fuente origial: Nature Communications. 13 (1): 122-
    Referencia de l'ítem segons les normes APA: Rapisardi, Giacomo; Kryven, Ivan; Arenas, Alex (2022). Percolation in networks with local homeostatic plasticity. Nature Communications, 13(1), 122-. DOI: 10.1038/s41467-021-27736-0
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI del artículo: 10.1038/s41467-021-27736-0
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2022
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Biochemistry, Genetics and Molecular Biology (Miscellaneous),Chemistry (Miscellaneous),Multidisciplinary Sciences,Physics and Astronomy (Miscellaneous)
    Algorithms
    Animals
    Computer simulation
    Homeostasis
    Humans
    Models, statistical
    Nerve net
    Neural networks, computer
    Antropologia / arqueologia
    Astronomia / física
    Biochemistry, genetics and molecular biology (all)
    Biochemistry, genetics and molecular biology (miscellaneous)
    Biodiversidade
    Biotecnología
    Chemistry (all)
    Chemistry (miscellaneous)
    Ciência da computação
    Ciências agrárias i
    Ciências ambientais
    Ciências biológicas i
    Ciências biológicas ii
    Ciências biológicas iii
    Educação física
    Engenharias iv
    Farmacia
    General biochemistry,genetics and molecular biology
    General chemistry
    General medicine
    General physics and astronomy
    Geociências
    Interdisciplinar
    Matemática / probabilidade e estatística
    Materiais
    Medicina i
    Medicina ii
    Medicina iii
    Medicina veterinaria
    Multidisciplinary
    Multidisciplinary sciences
    Nutrição
    Odontología
    Physics and astronomy (all)
    Physics and astronomy (miscellaneous)
    Planejamento urbano e regional / demografia
    Psicología
    Química
    Saúde coletiva
    Zootecnia / recursos pesqueiros
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