Box scaling as a proxy of finite size correlations

Autores
Martin, Daniel Alejandro; Ribeiro, Tiago L.; Cannas, Sergio A.; Grigera, Tomás Sebastián; Plenz, Dietmar; Chialvo, Dante R.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Facultad de Ciencias Exactas
Instituto de Física de Líquidos y Sistemas Biológicos
Materia
Física
Computational biology and bioinformatics
Mathematics and computing
Neuroscience
Physics
Statistical physics, thermodynamics and nonlinear dynamics
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/135393

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spelling Box scaling as a proxy of finite size correlationsMartin, Daniel AlejandroRibeiro, Tiago L.Cannas, Sergio A.Grigera, Tomás SebastiánPlenz, DietmarChialvo, Dante R.FísicaComputational biology and bioinformaticsMathematics and computingNeurosciencePhysicsStatistical physics, thermodynamics and nonlinear dynamicsThe 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.Facultad de Ciencias ExactasInstituto de Física de Líquidos y Sistemas Biológicos2021-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/135393enginfo:eu-repo/semantics/altIdentifier/issn/2045-2322info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-021-95595-2info:eu-repo/semantics/altIdentifier/pmid/34354220info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:31:57Zoai:sedici.unlp.edu.ar:10915/135393Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:31:57.466SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Box scaling as a proxy of finite size correlations
title Box scaling as a proxy of finite size correlations
spellingShingle Box scaling as a proxy of finite size correlations
Martin, Daniel Alejandro
Física
Computational biology and bioinformatics
Mathematics and computing
Neuroscience
Physics
Statistical physics, thermodynamics and nonlinear dynamics
title_short Box scaling as a proxy of finite size correlations
title_full Box scaling as a proxy of finite size correlations
title_fullStr Box scaling as a proxy of finite size correlations
title_full_unstemmed Box scaling as a proxy of finite size correlations
title_sort Box scaling as a proxy of finite size correlations
dc.creator.none.fl_str_mv Martin, Daniel Alejandro
Ribeiro, Tiago L.
Cannas, Sergio A.
Grigera, Tomás Sebastián
Plenz, Dietmar
Chialvo, Dante R.
author Martin, Daniel Alejandro
author_facet Martin, Daniel Alejandro
Ribeiro, Tiago L.
Cannas, Sergio A.
Grigera, Tomás Sebastián
Plenz, Dietmar
Chialvo, Dante R.
author_role author
author2 Ribeiro, Tiago L.
Cannas, Sergio A.
Grigera, Tomás Sebastián
Plenz, Dietmar
Chialvo, Dante R.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Física
Computational biology and bioinformatics
Mathematics and computing
Neuroscience
Physics
Statistical physics, thermodynamics and nonlinear dynamics
topic Física
Computational biology and bioinformatics
Mathematics and computing
Neuroscience
Physics
Statistical physics, thermodynamics and nonlinear dynamics
dc.description.none.fl_txt_mv 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.
Facultad de Ciencias Exactas
Instituto de Física de Líquidos y Sistemas Biológicos
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021-08
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info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-021-95595-2
info:eu-repo/semantics/altIdentifier/pmid/34354220
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
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