Dynamics and reliability of bistable neurons driven with time-dependent stimuli
- Autores
- Gonzalo Cogno, Ximena Soledad; Schreiber, Susanne; Samengo, Ines
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The reliability of a spiking neuron depends on the frequency content of the driving input signal. Previous studies have shown that well above threshold, regularly firing neurons generate reliable responses when the input signal resonates with the firing frequency of the cell. Instead, well below threshold, reliable responses are obtained when the input frequency resonates with the subthreshold oscillations of the neuron. Previous theories, however, provide no clear prediction for the input frequency giving rise to maximally reliable spiking at threshold, which is probably the most relevant firing regime in mammalian cortex under physiological conditions. In particular, when the firing onset is governed by a subcritical Hopf bifurcation, the frequency of subthreshold oscillations often differs from the firing rate at threshold. The predictions of previous studies, hence, cannot be smoothly merged at threshold. Here we explore the behavior of reliability in bistable neurons near threshold using three types of driving stimuli: constant, periodic and stochastic. We find that the two natural frequencies of the system, associated to the two coexisting attractors, provide a rich variety of possible locking modes with the external signal. Reliability is determined by the sensitivity to noise of each locking mode, and also by the transition probabilities between modes. Noise increases the amount of spike-time jitter, and minimal jitter is obtained for input frequencies coinciding with the suprathreshold firing rate of the cell. In addition, noise may either enhance or inhibit transitions between the two attractors, depending on the input frequency. The dual role played by noise in bistable systems implies that reliability is determined by a delicate balance between spike-time jitter and the rate of transitions between attractors.
Fil: Gonzalo Cogno, Ximena Soledad. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Schreiber, Susanne. Center for Computational Neuroscience, Humboldt Universit ̈at zu Berlin and Bernstein; Alemania
Fil: Samengo, Ines. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina - Materia
-
Reliability
Bistable Neurons
Type Ii Morris Lecar
Dynamical Systems - 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:11336/21388
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Dynamics and reliability of bistable neurons driven with time-dependent stimuliGonzalo Cogno, Ximena SoledadSchreiber, SusanneSamengo, InesReliabilityBistable NeuronsType Ii Morris LecarDynamical Systemshttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The reliability of a spiking neuron depends on the frequency content of the driving input signal. Previous studies have shown that well above threshold, regularly firing neurons generate reliable responses when the input signal resonates with the firing frequency of the cell. Instead, well below threshold, reliable responses are obtained when the input frequency resonates with the subthreshold oscillations of the neuron. Previous theories, however, provide no clear prediction for the input frequency giving rise to maximally reliable spiking at threshold, which is probably the most relevant firing regime in mammalian cortex under physiological conditions. In particular, when the firing onset is governed by a subcritical Hopf bifurcation, the frequency of subthreshold oscillations often differs from the firing rate at threshold. The predictions of previous studies, hence, cannot be smoothly merged at threshold. Here we explore the behavior of reliability in bistable neurons near threshold using three types of driving stimuli: constant, periodic and stochastic. We find that the two natural frequencies of the system, associated to the two coexisting attractors, provide a rich variety of possible locking modes with the external signal. Reliability is determined by the sensitivity to noise of each locking mode, and also by the transition probabilities between modes. Noise increases the amount of spike-time jitter, and minimal jitter is obtained for input frequencies coinciding with the suprathreshold firing rate of the cell. In addition, noise may either enhance or inhibit transitions between the two attractors, depending on the input frequency. The dual role played by noise in bistable systems implies that reliability is determined by a delicate balance between spike-time jitter and the rate of transitions between attractors.Fil: Gonzalo Cogno, Ximena Soledad. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schreiber, Susanne. Center for Computational Neuroscience, Humboldt Universit ̈at zu Berlin and Bernstein; AlemaniaFil: Samengo, Ines. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaM I T Press2014-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/21388Gonzalo Cogno, Ximena Soledad; Schreiber, Susanne; Samengo, Ines; Dynamics and reliability of bistable neurons driven with time-dependent stimuli; M I T Press; Neural Computation; 26; 12; 1-12-2014; 2798-28260899-7667CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.mitpressjournals.org/doi/10.1162/NECO_a_00671info:eu-repo/semantics/altIdentifier/doi/10.1162/NECO_a_00671info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:58:07Zoai:ri.conicet.gov.ar:11336/21388instacron: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:34982025-09-03 09:58:07.365CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
title |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
spellingShingle |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli Gonzalo Cogno, Ximena Soledad Reliability Bistable Neurons Type Ii Morris Lecar Dynamical Systems |
title_short |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
title_full |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
title_fullStr |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
title_full_unstemmed |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
title_sort |
Dynamics and reliability of bistable neurons driven with time-dependent stimuli |
dc.creator.none.fl_str_mv |
Gonzalo Cogno, Ximena Soledad Schreiber, Susanne Samengo, Ines |
author |
Gonzalo Cogno, Ximena Soledad |
author_facet |
Gonzalo Cogno, Ximena Soledad Schreiber, Susanne Samengo, Ines |
author_role |
author |
author2 |
Schreiber, Susanne Samengo, Ines |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Reliability Bistable Neurons Type Ii Morris Lecar Dynamical Systems |
topic |
Reliability Bistable Neurons Type Ii Morris Lecar Dynamical Systems |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
The reliability of a spiking neuron depends on the frequency content of the driving input signal. Previous studies have shown that well above threshold, regularly firing neurons generate reliable responses when the input signal resonates with the firing frequency of the cell. Instead, well below threshold, reliable responses are obtained when the input frequency resonates with the subthreshold oscillations of the neuron. Previous theories, however, provide no clear prediction for the input frequency giving rise to maximally reliable spiking at threshold, which is probably the most relevant firing regime in mammalian cortex under physiological conditions. In particular, when the firing onset is governed by a subcritical Hopf bifurcation, the frequency of subthreshold oscillations often differs from the firing rate at threshold. The predictions of previous studies, hence, cannot be smoothly merged at threshold. Here we explore the behavior of reliability in bistable neurons near threshold using three types of driving stimuli: constant, periodic and stochastic. We find that the two natural frequencies of the system, associated to the two coexisting attractors, provide a rich variety of possible locking modes with the external signal. Reliability is determined by the sensitivity to noise of each locking mode, and also by the transition probabilities between modes. Noise increases the amount of spike-time jitter, and minimal jitter is obtained for input frequencies coinciding with the suprathreshold firing rate of the cell. In addition, noise may either enhance or inhibit transitions between the two attractors, depending on the input frequency. The dual role played by noise in bistable systems implies that reliability is determined by a delicate balance between spike-time jitter and the rate of transitions between attractors. Fil: Gonzalo Cogno, Ximena Soledad. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Schreiber, Susanne. Center for Computational Neuroscience, Humboldt Universit ̈at zu Berlin and Bernstein; Alemania Fil: Samengo, Ines. Comisión Nacional de Energía Atomica. Gerencia del _rea de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadistica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina |
description |
The reliability of a spiking neuron depends on the frequency content of the driving input signal. Previous studies have shown that well above threshold, regularly firing neurons generate reliable responses when the input signal resonates with the firing frequency of the cell. Instead, well below threshold, reliable responses are obtained when the input frequency resonates with the subthreshold oscillations of the neuron. Previous theories, however, provide no clear prediction for the input frequency giving rise to maximally reliable spiking at threshold, which is probably the most relevant firing regime in mammalian cortex under physiological conditions. In particular, when the firing onset is governed by a subcritical Hopf bifurcation, the frequency of subthreshold oscillations often differs from the firing rate at threshold. The predictions of previous studies, hence, cannot be smoothly merged at threshold. Here we explore the behavior of reliability in bistable neurons near threshold using three types of driving stimuli: constant, periodic and stochastic. We find that the two natural frequencies of the system, associated to the two coexisting attractors, provide a rich variety of possible locking modes with the external signal. Reliability is determined by the sensitivity to noise of each locking mode, and also by the transition probabilities between modes. Noise increases the amount of spike-time jitter, and minimal jitter is obtained for input frequencies coinciding with the suprathreshold firing rate of the cell. In addition, noise may either enhance or inhibit transitions between the two attractors, depending on the input frequency. The dual role played by noise in bistable systems implies that reliability is determined by a delicate balance between spike-time jitter and the rate of transitions between attractors. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-01 |
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/11336/21388 Gonzalo Cogno, Ximena Soledad; Schreiber, Susanne; Samengo, Ines; Dynamics and reliability of bistable neurons driven with time-dependent stimuli; M I T Press; Neural Computation; 26; 12; 1-12-2014; 2798-2826 0899-7667 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/21388 |
identifier_str_mv |
Gonzalo Cogno, Ximena Soledad; Schreiber, Susanne; Samengo, Ines; Dynamics and reliability of bistable neurons driven with time-dependent stimuli; M I T Press; Neural Computation; 26; 12; 1-12-2014; 2798-2826 0899-7667 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.mitpressjournals.org/doi/10.1162/NECO_a_00671 info:eu-repo/semantics/altIdentifier/doi/10.1162/NECO_a_00671 |
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 |
M I T Press |
publisher.none.fl_str_mv |
M I T Press |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
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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1842269501697032192 |
score |
13.13397 |