Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems

Autores
Martinez, Nataniel; Deza, Roberto; Montani, Fernando Fabián
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purkinje cells exhibit a reduction of the mean firing rate at intermediate-noise intensities, which is somewhat reminiscent of the response enhancement known as “stochastic resonance” (SR). Although the comparison with the stochastic resonance ends here, the current phenomenon has been given the name “inverse stochastic resonance” (ISR). Recent research has demonstrated that the ISR effect, like its close relative “nonstandard SR” [or, more correctly, noise-induced activity amplification (NIAA)], has been shown to stem from the weak-noise quenching of the initial distribution, in bistable regimes where the metastable state has a larger attraction basin than the global minimum. To understand the underlying mechanism of the ISR and NIAA phenomena, we study the probability distribution function of a one-dimensional system subjected to a bistable potential that has the property of symmetry, i.e., if we change the sign of one of its parameters, we can obtain both phenomena with the same properties in the depth of the wells and the width of their basins of attraction subjected to Gaussian white noise with variable intensity. Previous work has shown that one can theoretically determine the probability distribution function using the convex sum between the behavior at small and high noise intensities. To determine the probability distribution function more precisely, we resort to the “weighted ensemble Brownian dynamics simulation” model, which provides an accurate estimate of the probability distribution function for both low and high noise intensities and, most importantly, for the transition of both behaviors. In this way, on the one hand, we show that both phenomena emerge from a metastable system where, in the case of ISR, the global minimum of the system is in a state of lower activity, while in the case of NIAA, the global minimum is in a state of increased activity, the importance of which does not depend on the width of the basins of attraction. On the other hand, we see that quantifiers such as Fisher information, statistical complexity, and especially Shannon entropy fail to distinguish them, but they show the existence of the mentioned phenomena. Thus, noise management may well be a mechanism by which Purkinje cells find an efficient way to transmit information in the cerebral cortex.
Instituto de Física La Plata
Materia
Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/160847

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spelling Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systemsMartinez, NatanielDeza, RobertoMontani, Fernando FabiánFísicaPurkinje cellsstochastic resonanceinverse stochastic resonancenoise-induced activity amplificationweighted ensemble Brownian dynamics simulation” modelPurkinje cells exhibit a reduction of the mean firing rate at intermediate-noise intensities, which is somewhat reminiscent of the response enhancement known as “stochastic resonance” (SR). Although the comparison with the stochastic resonance ends here, the current phenomenon has been given the name “inverse stochastic resonance” (ISR). Recent research has demonstrated that the ISR effect, like its close relative “nonstandard SR” [or, more correctly, noise-induced activity amplification (NIAA)], has been shown to stem from the weak-noise quenching of the initial distribution, in bistable regimes where the metastable state has a larger attraction basin than the global minimum. To understand the underlying mechanism of the ISR and NIAA phenomena, we study the probability distribution function of a one-dimensional system subjected to a bistable potential that has the property of symmetry, i.e., if we change the sign of one of its parameters, we can obtain both phenomena with the same properties in the depth of the wells and the width of their basins of attraction subjected to Gaussian white noise with variable intensity. Previous work has shown that one can theoretically determine the probability distribution function using the convex sum between the behavior at small and high noise intensities. To determine the probability distribution function more precisely, we resort to the “weighted ensemble Brownian dynamics simulation” model, which provides an accurate estimate of the probability distribution function for both low and high noise intensities and, most importantly, for the transition of both behaviors. In this way, on the one hand, we show that both phenomena emerge from a metastable system where, in the case of ISR, the global minimum of the system is in a state of lower activity, while in the case of NIAA, the global minimum is in a state of increased activity, the importance of which does not depend on the width of the basins of attraction. On the other hand, we see that quantifiers such as Fisher information, statistical complexity, and especially Shannon entropy fail to distinguish them, but they show the existence of the mentioned phenomena. Thus, noise management may well be a mechanism by which Purkinje cells find an efficient way to transmit information in the cerebral cortex.Instituto de Física La Plata2023-05-02info: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/10915/160847enginfo:eu-repo/semantics/altIdentifier/issn/2470-0053info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.107.054402info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:42:01Zoai:sedici.unlp.edu.ar:10915/160847Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:42:01.648SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
title Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
spellingShingle Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
Martinez, Nataniel
Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
title_short Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
title_full Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
title_fullStr Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
title_full_unstemmed Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
title_sort Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
dc.creator.none.fl_str_mv Martinez, Nataniel
Deza, Roberto
Montani, Fernando Fabián
author Martinez, Nataniel
author_facet Martinez, Nataniel
Deza, Roberto
Montani, Fernando Fabián
author_role author
author2 Deza, Roberto
Montani, Fernando Fabián
author2_role author
author
dc.subject.none.fl_str_mv Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
topic Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
dc.description.none.fl_txt_mv Purkinje cells exhibit a reduction of the mean firing rate at intermediate-noise intensities, which is somewhat reminiscent of the response enhancement known as “stochastic resonance” (SR). Although the comparison with the stochastic resonance ends here, the current phenomenon has been given the name “inverse stochastic resonance” (ISR). Recent research has demonstrated that the ISR effect, like its close relative “nonstandard SR” [or, more correctly, noise-induced activity amplification (NIAA)], has been shown to stem from the weak-noise quenching of the initial distribution, in bistable regimes where the metastable state has a larger attraction basin than the global minimum. To understand the underlying mechanism of the ISR and NIAA phenomena, we study the probability distribution function of a one-dimensional system subjected to a bistable potential that has the property of symmetry, i.e., if we change the sign of one of its parameters, we can obtain both phenomena with the same properties in the depth of the wells and the width of their basins of attraction subjected to Gaussian white noise with variable intensity. Previous work has shown that one can theoretically determine the probability distribution function using the convex sum between the behavior at small and high noise intensities. To determine the probability distribution function more precisely, we resort to the “weighted ensemble Brownian dynamics simulation” model, which provides an accurate estimate of the probability distribution function for both low and high noise intensities and, most importantly, for the transition of both behaviors. In this way, on the one hand, we show that both phenomena emerge from a metastable system where, in the case of ISR, the global minimum of the system is in a state of lower activity, while in the case of NIAA, the global minimum is in a state of increased activity, the importance of which does not depend on the width of the basins of attraction. On the other hand, we see that quantifiers such as Fisher information, statistical complexity, and especially Shannon entropy fail to distinguish them, but they show the existence of the mentioned phenomena. Thus, noise management may well be a mechanism by which Purkinje cells find an efficient way to transmit information in the cerebral cortex.
Instituto de Física La Plata
description Purkinje cells exhibit a reduction of the mean firing rate at intermediate-noise intensities, which is somewhat reminiscent of the response enhancement known as “stochastic resonance” (SR). Although the comparison with the stochastic resonance ends here, the current phenomenon has been given the name “inverse stochastic resonance” (ISR). Recent research has demonstrated that the ISR effect, like its close relative “nonstandard SR” [or, more correctly, noise-induced activity amplification (NIAA)], has been shown to stem from the weak-noise quenching of the initial distribution, in bistable regimes where the metastable state has a larger attraction basin than the global minimum. To understand the underlying mechanism of the ISR and NIAA phenomena, we study the probability distribution function of a one-dimensional system subjected to a bistable potential that has the property of symmetry, i.e., if we change the sign of one of its parameters, we can obtain both phenomena with the same properties in the depth of the wells and the width of their basins of attraction subjected to Gaussian white noise with variable intensity. Previous work has shown that one can theoretically determine the probability distribution function using the convex sum between the behavior at small and high noise intensities. To determine the probability distribution function more precisely, we resort to the “weighted ensemble Brownian dynamics simulation” model, which provides an accurate estimate of the probability distribution function for both low and high noise intensities and, most importantly, for the transition of both behaviors. In this way, on the one hand, we show that both phenomena emerge from a metastable system where, in the case of ISR, the global minimum of the system is in a state of lower activity, while in the case of NIAA, the global minimum is in a state of increased activity, the importance of which does not depend on the width of the basins of attraction. On the other hand, we see that quantifiers such as Fisher information, statistical complexity, and especially Shannon entropy fail to distinguish them, but they show the existence of the mentioned phenomena. Thus, noise management may well be a mechanism by which Purkinje cells find an efficient way to transmit information in the cerebral cortex.
publishDate 2023
dc.date.none.fl_str_mv 2023-05-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/160847
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2470-0053
info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.107.054402
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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