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

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 nam...

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Autores principales: Martinez, Nataniel, Deza, Roberto, Montani, Fernando Fabián
Formato: Articulo
Lenguaje:Inglés
Publicado: 2023
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Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/160847
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spelling I19-R120-10915-1608472023-11-29T20:07:31Z http://sedici.unlp.edu.ar/handle/10915/160847 Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems Martinez, Nataniel Deza, Roberto Montani, Fernando Fabián 2023-05-02 2023-11-29T13:14:11Z en Física Purkinje cells stochastic resonance inverse stochastic resonance noise-induced activity amplification weighted ensemble Brownian dynamics simulation” model 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 Articulo Articulo http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
spellingShingle Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
Martinez, Nataniel
Deza, Roberto
Montani, Fernando Fabián
Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
topic_facet Física
Purkinje cells
stochastic resonance
inverse stochastic resonance
noise-induced activity amplification
weighted ensemble Brownian dynamics simulation” model
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.
format Articulo
Articulo
author Martinez, Nataniel
Deza, Roberto
Montani, Fernando Fabián
author_facet Martinez, Nataniel
Deza, Roberto
Montani, Fernando Fabián
author_sort Martinez, Nataniel
title Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems
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
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/160847
work_keys_str_mv AT martineznataniel characterizingtheinformationtransmissionofinversestochasticresonanceandnoiseinducedactivityamplificationinneuronalsystems
AT dezaroberto characterizingtheinformationtransmissionofinversestochasticresonanceandnoiseinducedactivityamplificationinneuronalsystems
AT montanifernandofabian characterizingtheinformationtransmissionofinversestochasticresonanceandnoiseinducedactivityamplificationinneuronalsystems
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