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Box scaling as a proxy of finite size correlations.
Martin, Daniel A; Ribeiro, Tiago L; Cannas, Sergio A; Grigera, Tomas S; Plenz, Dietmar; Chialvo, Dante R.
Afiliação
  • Martin DA; Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de Gral. San Martín, Campus Miguelete, 25 de Mayo y Francia, 1650, San Martín, Buenos Aires, Argentina. danielalejandromartin@gmail.com.
  • Ribeiro TL; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina. danielalejandromartin@gmail.com.
  • Cannas SA; Section on Critical Brain Dynamics, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Grigera TS; Instituto de Física Enrique Gaviola (IFEG-CONICET), Facultad de Matemática Astronomía Física y Computación, Universidad Nacional de Córdoba, 5000, Córdoba, Argentina.
  • Plenz D; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, 1425, Buenos Aires, Argentina.
  • Chialvo DR; Instituto de Física de Líquidos y Sistemas Biológicos (IFLySiB-CONICET), Universidad Nacional de La Plata, 1900, La Plata, Buenos Aires, Argentina.
Sci Rep ; 11(1): 15937, 2021 08 05.
Article em En | MEDLINE | ID: mdl-34354220
The scaling of correlations as a function of size provides important hints to understand critical phenomena on a variety of systems. Its study in biological structures offers two challenges: usually they are not of infinite size, and, in the majority of cases, dimensions can not be varied at will. Here we discuss how finite-size scaling can be approximated in an experimental system of fixed and relatively small extent, by computing correlations inside of a reduced field of view of various widths (we will refer to this procedure as "box-scaling"). A relation among the size of the field of view, and measured correlation length, is derived at, and away from, the critical regime. Numerical simulations of a neuronal network, as well as the ferromagnetic 2D Ising model, are used to verify such approximations. Numerical results support the validity of the heuristic approach, which should be useful to characterize relevant aspects of critical phenomena in biological systems.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argentina País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argentina País de publicação: Reino Unido