Spatio-temporal correlations in models of collective motion ruled by different dynamical laws
- Autores
- Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas Sebastian; Melillo, Stefania; Viale, Massimiliano
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.
Fil: Cavagna, Andrea. Consiglio Nazionale delle Ricerche; Italia
Fil: Conti, Daniele. Università degli studi di Roma "La Sapienza"; Italia
Fil: Giardina, Irene. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; Italia
Fil: Grigera, Tomas Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física de Líquidos y Sistemas Biológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina
Fil: Melillo, Stefania. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; Italia
Fil: Viale, Massimiliano. Consiglio Nazionale delle Ricerche; Italia. Università degli studi di Roma "La Sapienza"; Italia - Materia
-
Biological Physics
Collective Behavior
Information Transfer
Spatio-Temporal Correlations
Statistical Mechanics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/47976
Ver los metadatos del registro completo
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Spatio-temporal correlations in models of collective motion ruled by different dynamical lawsCavagna, AndreaConti, DanieleGiardina, IreneGrigera, Tomas SebastianMelillo, StefaniaViale, MassimilianoBiological PhysicsCollective BehaviorInformation TransferSpatio-Temporal CorrelationsStatistical Mechanicshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.Fil: Cavagna, Andrea. Consiglio Nazionale delle Ricerche; ItaliaFil: Conti, Daniele. Università degli studi di Roma "La Sapienza"; ItaliaFil: Giardina, Irene. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; ItaliaFil: Grigera, Tomas Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física de Líquidos y Sistemas Biológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física de Líquidos y Sistemas Biológicos; ArgentinaFil: Melillo, Stefania. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; ItaliaFil: Viale, Massimiliano. Consiglio Nazionale delle Ricerche; Italia. Università degli studi di Roma "La Sapienza"; ItaliaIOP Publishing2016-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/47976Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas Sebastian; Melillo, Stefania; et al.; Spatio-temporal correlations in models of collective motion ruled by different dynamical laws; IOP Publishing; Physical Biology; 13; 6; 11-2016; 1-21; 0650011478-3967CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1088/1478-3975/13/6/065001info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1478-3975/13/6/065001/metainfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:43:21Zoai:ri.conicet.gov.ar:11336/47976instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:43:21.785CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
spellingShingle |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws Cavagna, Andrea Biological Physics Collective Behavior Information Transfer Spatio-Temporal Correlations Statistical Mechanics |
title_short |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_full |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_fullStr |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_full_unstemmed |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_sort |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
dc.creator.none.fl_str_mv |
Cavagna, Andrea Conti, Daniele Giardina, Irene Grigera, Tomas Sebastian Melillo, Stefania Viale, Massimiliano |
author |
Cavagna, Andrea |
author_facet |
Cavagna, Andrea Conti, Daniele Giardina, Irene Grigera, Tomas Sebastian Melillo, Stefania Viale, Massimiliano |
author_role |
author |
author2 |
Conti, Daniele Giardina, Irene Grigera, Tomas Sebastian Melillo, Stefania Viale, Massimiliano |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Biological Physics Collective Behavior Information Transfer Spatio-Temporal Correlations Statistical Mechanics |
topic |
Biological Physics Collective Behavior Information Transfer Spatio-Temporal Correlations Statistical Mechanics |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.3 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model. Fil: Cavagna, Andrea. Consiglio Nazionale delle Ricerche; Italia Fil: Conti, Daniele. Università degli studi di Roma "La Sapienza"; Italia Fil: Giardina, Irene. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; Italia Fil: Grigera, Tomas Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física de Líquidos y Sistemas Biológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina Fil: Melillo, Stefania. Università degli studi di Roma "La Sapienza"; Italia. Consiglio Nazionale delle Ricerche; Italia Fil: Viale, Massimiliano. Consiglio Nazionale delle Ricerche; Italia. Università degli studi di Roma "La Sapienza"; Italia |
description |
Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-11 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/47976 Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas Sebastian; Melillo, Stefania; et al.; Spatio-temporal correlations in models of collective motion ruled by different dynamical laws; IOP Publishing; Physical Biology; 13; 6; 11-2016; 1-21; 065001 1478-3967 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/47976 |
identifier_str_mv |
Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas Sebastian; Melillo, Stefania; et al.; Spatio-temporal correlations in models of collective motion ruled by different dynamical laws; IOP Publishing; Physical Biology; 13; 6; 11-2016; 1-21; 065001 1478-3967 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1088/1478-3975/13/6/065001 info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1478-3975/13/6/065001/meta |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
IOP Publishing |
publisher.none.fl_str_mv |
IOP Publishing |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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