Causal information quantification of prominent dynamical features of biological neurons
- Autores
- Montani, Fernando Fabián; Baravalle, Román; Montangie, Lisandro; Rosso, Osvaldo A.
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Neurons tend to fire a spike when they are near a bifurcation from the resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition that determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation. Moreover, the biophysics and the dynamics behind it can usually be described through a phase diagram that involves membrane voltage versus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, which takes into account the fine temporal structures of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties of neurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: statistical complexity versus Fisher information versus Shannon entropy.
Instituto de Física de Líquidos y Sistemas Biológicos - Materia
-
Física
Entropy
Fisher information measure
Neurons
Statistical complexity - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/86925
Ver los metadatos del registro completo
id |
SEDICI_c36a707c4143c30da5a2143989da0d1e |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/86925 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
spelling |
Causal information quantification of prominent dynamical features of biological neuronsMontani, Fernando FabiánBaravalle, RománMontangie, LisandroRosso, Osvaldo A.FísicaEntropyFisher information measureNeuronsStatistical complexityNeurons tend to fire a spike when they are near a bifurcation from the resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition that determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation. Moreover, the biophysics and the dynamics behind it can usually be described through a phase diagram that involves membrane voltage versus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, which takes into account the fine temporal structures of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties of neurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: statistical complexity versus Fisher information versus Shannon entropy.Instituto de Física de Líquidos y Sistemas Biológicos2015info: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/10915/86925enginfo:eu-repo/semantics/altIdentifier/issn/1364-503Xinfo:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2015.0109info: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:UNLP2025-09-29T11:16:50Zoai:sedici.unlp.edu.ar:10915/86925Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:16:50.672SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Causal information quantification of prominent dynamical features of biological neurons |
title |
Causal information quantification of prominent dynamical features of biological neurons |
spellingShingle |
Causal information quantification of prominent dynamical features of biological neurons Montani, Fernando Fabián Física Entropy Fisher information measure Neurons Statistical complexity |
title_short |
Causal information quantification of prominent dynamical features of biological neurons |
title_full |
Causal information quantification of prominent dynamical features of biological neurons |
title_fullStr |
Causal information quantification of prominent dynamical features of biological neurons |
title_full_unstemmed |
Causal information quantification of prominent dynamical features of biological neurons |
title_sort |
Causal information quantification of prominent dynamical features of biological neurons |
dc.creator.none.fl_str_mv |
Montani, Fernando Fabián Baravalle, Román Montangie, Lisandro Rosso, Osvaldo A. |
author |
Montani, Fernando Fabián |
author_facet |
Montani, Fernando Fabián Baravalle, Román Montangie, Lisandro Rosso, Osvaldo A. |
author_role |
author |
author2 |
Baravalle, Román Montangie, Lisandro Rosso, Osvaldo A. |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Física Entropy Fisher information measure Neurons Statistical complexity |
topic |
Física Entropy Fisher information measure Neurons Statistical complexity |
dc.description.none.fl_txt_mv |
Neurons tend to fire a spike when they are near a bifurcation from the resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition that determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation. Moreover, the biophysics and the dynamics behind it can usually be described through a phase diagram that involves membrane voltage versus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, which takes into account the fine temporal structures of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties of neurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: statistical complexity versus Fisher information versus Shannon entropy. Instituto de Física de Líquidos y Sistemas Biológicos |
description |
Neurons tend to fire a spike when they are near a bifurcation from the resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition that determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation. Moreover, the biophysics and the dynamics behind it can usually be described through a phase diagram that involves membrane voltage versus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, which takes into account the fine temporal structures of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties of neurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: statistical complexity versus Fisher information versus Shannon entropy. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 |
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/10915/86925 |
url |
http://sedici.unlp.edu.ar/handle/10915/86925 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1364-503X info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2015.0109 |
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 |
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 |
_version_ |
1844616041370484736 |
score |
13.070432 |