Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity

Autores
Montangie, Lisandro; Montani, Fernando Fabián
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Experiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronalpopulations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random walk processes with q-Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.
Instituto de Física de Líquidos y Sistemas Biológicos
Materia
Física
Common inputs
Membrane potential
Quiescent states
Higher-order correlations
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:10915/100075
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/100075
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activityMontangie, LisandroMontani, Fernando FabiánFísicaCommon inputsMembrane potentialQuiescent statesHigher-order correlationsExperiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronalpopulations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random walk processes with q-Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.Instituto de Física de Líquidos y Sistemas Biológicos2018-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf60302-60308http://sedici.unlp.edu.ar/handle/10915/100075enginfo:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/90683info:eu-repo/semantics/altIdentifier/url/https://link.aps.org/doi/10.1103/PhysRevE.97.060302info:eu-repo/semantics/altIdentifier/issn/1539-3755info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.97.060302info:eu-repo/semantics/altIdentifier/hdl/11336/90683info: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:UNLP2025-09-29T11:20:35Zoai:sedici.unlp.edu.ar:10915/100075Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:20:36.042SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
title Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
spellingShingle Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
Montangie, Lisandro
Física
Common inputs
Membrane potential
Quiescent states
Higher-order correlations
title_short Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
title_full Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
title_fullStr Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
title_full_unstemmed Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
title_sort Common inputs in subthreshold membrane potential: the role of quiescent states in neuronal activity
dc.creator.none.fl_str_mv Montangie, Lisandro
Montani, Fernando Fabián
author Montangie, Lisandro
author_facet Montangie, Lisandro
Montani, Fernando Fabián
author_role author
author2 Montani, Fernando Fabián
author2_role author
dc.subject.none.fl_str_mv Física
Common inputs
Membrane potential
Quiescent states
Higher-order correlations
topic Física
Common inputs
Membrane potential
Quiescent states
Higher-order correlations
dc.description.none.fl_txt_mv Experiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronalpopulations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random walk processes with q-Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.
Instituto de Física de Líquidos y Sistemas Biológicos
description Experiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronalpopulations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random walk processes with q-Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.
publishDate 2018
dc.date.none.fl_str_mv 2018-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/100075
url http://sedici.unlp.edu.ar/handle/10915/100075
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/90683
info:eu-repo/semantics/altIdentifier/url/https://link.aps.org/doi/10.1103/PhysRevE.97.060302
info:eu-repo/semantics/altIdentifier/issn/1539-3755
info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.97.060302
info:eu-repo/semantics/altIdentifier/hdl/11336/90683
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)
dc.format.none.fl_str_mv application/pdf
60302-60308
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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