Articles producció científica> Enginyeria Informàtica i Matemàtiques

Percolation in networks with local homeostatic plasticity

  • Dades identificatives

    Identificador: imarina:9381081
    Autors:
    Rapisardi, GiacomoKryven, IvanArenas, Alex
    Resum:
    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.
  • Altres:

    Autor segons l'article: Rapisardi, Giacomo; Kryven, Ivan; Arenas, Alex
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Arenas Moreno, Alejandro / Rapisardi, Giacomo
    Paraules clau: Algorithms Animals Computer simulation Homeostasis Humans Models, statistical Nerve net Neural networks, computer
    Resum: 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.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: alexandre.arenas@urv.cat
    Identificador de l'autor: 0000-0003-0937-0334
    Data d'alta del registre: 2024-09-28
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.nature.com/articles/s41467-021-27736-0
    Referència a l'article segons font original: Nature Communications. 13 (1): 122-
    Referència 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 Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI de l'article: 10.1038/s41467-021-27736-0
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2022
    Tipus de publicació: Journal Publications
  • Paraules clau:

    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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