The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex

Autores
Montani, Fernando Fabián; Ince, Rob A. A.; Senatore, Riccardo; Arabzadeh, Ehsan; Diamond, Mathew E.; Panzeri, Stefano
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Understanding the operations of neural networks in the brain requires an understanding of whether interactions among neurons can be described by a pairwise interaction model, or whether a higher order interaction model is needed. In this article we consider the rate of synchronous discharge of a local population of neurons, a macroscopic index of the activation of the neural network that can be measured experimentally. We analyse a model based on physics’ maximum entropy principle that evaluates whether the probability of synchronous discharge can be described by interactions up to any given order. When compared with real neural population activity obtained from the rat somatosensory cortex, the model shows that interactions of at least order three or four are necessary to explain the data. We use Shannon information to compute the impact of high-order correlations on the amount of somatosensory information transmitted by the rate of synchronous discharge, and we find that correlations of higher order progressively decrease the information available through the neural population. These results are compatible with the hypothesis that high-order interactions play a role in shaping the dynamics of neural networks, and that they should be taken into account when computing the representational capacity of neural populations.
Facultad de Ciencias Exactas
Materia
Física
Ciencias Médicas
spike synchronization
cortex
information geometry
maximum entropy
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:10915/160254

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network_name_str SEDICI (UNLP)
spelling The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortexMontani, Fernando FabiánInce, Rob A. A.Senatore, RiccardoArabzadeh, EhsanDiamond, Mathew E.Panzeri, StefanoFísicaCiencias Médicasspike synchronizationcortexinformation geometrymaximum entropyUnderstanding the operations of neural networks in the brain requires an understanding of whether interactions among neurons can be described by a pairwise interaction model, or whether a higher order interaction model is needed. In this article we consider the rate of synchronous discharge of a local population of neurons, a macroscopic index of the activation of the neural network that can be measured experimentally. We analyse a model based on physics’ maximum entropy principle that evaluates whether the probability of synchronous discharge can be described by interactions up to any given order. When compared with real neural population activity obtained from the rat somatosensory cortex, the model shows that interactions of at least order three or four are necessary to explain the data. We use Shannon information to compute the impact of high-order correlations on the amount of somatosensory information transmitted by the rate of synchronous discharge, and we find that correlations of higher order progressively decrease the information available through the neural population. These results are compatible with the hypothesis that high-order interactions play a role in shaping the dynamics of neural networks, and that they should be taken into account when computing the representational capacity of neural populations.Facultad de Ciencias Exactas2009info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf3297–3310http://sedici.unlp.edu.ar/handle/10915/160254enginfo:eu-repo/semantics/altIdentifier/issn/1364-503Xinfo:eu-repo/semantics/altIdentifier/issn/1471-2962info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2009.0082info: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:UNLP2025-09-29T11:41:57Zoai:sedici.unlp.edu.ar:10915/160254Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:41:57.481SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
title The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
spellingShingle The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
Montani, Fernando Fabián
Física
Ciencias Médicas
spike synchronization
cortex
information geometry
maximum entropy
title_short The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
title_full The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
title_fullStr The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
title_full_unstemmed The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
title_sort The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
dc.creator.none.fl_str_mv Montani, Fernando Fabián
Ince, Rob A. A.
Senatore, Riccardo
Arabzadeh, Ehsan
Diamond, Mathew E.
Panzeri, Stefano
author Montani, Fernando Fabián
author_facet Montani, Fernando Fabián
Ince, Rob A. A.
Senatore, Riccardo
Arabzadeh, Ehsan
Diamond, Mathew E.
Panzeri, Stefano
author_role author
author2 Ince, Rob A. A.
Senatore, Riccardo
Arabzadeh, Ehsan
Diamond, Mathew E.
Panzeri, Stefano
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Física
Ciencias Médicas
spike synchronization
cortex
information geometry
maximum entropy
topic Física
Ciencias Médicas
spike synchronization
cortex
information geometry
maximum entropy
dc.description.none.fl_txt_mv Understanding the operations of neural networks in the brain requires an understanding of whether interactions among neurons can be described by a pairwise interaction model, or whether a higher order interaction model is needed. In this article we consider the rate of synchronous discharge of a local population of neurons, a macroscopic index of the activation of the neural network that can be measured experimentally. We analyse a model based on physics’ maximum entropy principle that evaluates whether the probability of synchronous discharge can be described by interactions up to any given order. When compared with real neural population activity obtained from the rat somatosensory cortex, the model shows that interactions of at least order three or four are necessary to explain the data. We use Shannon information to compute the impact of high-order correlations on the amount of somatosensory information transmitted by the rate of synchronous discharge, and we find that correlations of higher order progressively decrease the information available through the neural population. These results are compatible with the hypothesis that high-order interactions play a role in shaping the dynamics of neural networks, and that they should be taken into account when computing the representational capacity of neural populations.
Facultad de Ciencias Exactas
description Understanding the operations of neural networks in the brain requires an understanding of whether interactions among neurons can be described by a pairwise interaction model, or whether a higher order interaction model is needed. In this article we consider the rate of synchronous discharge of a local population of neurons, a macroscopic index of the activation of the neural network that can be measured experimentally. We analyse a model based on physics’ maximum entropy principle that evaluates whether the probability of synchronous discharge can be described by interactions up to any given order. When compared with real neural population activity obtained from the rat somatosensory cortex, the model shows that interactions of at least order three or four are necessary to explain the data. We use Shannon information to compute the impact of high-order correlations on the amount of somatosensory information transmitted by the rate of synchronous discharge, and we find that correlations of higher order progressively decrease the information available through the neural population. These results are compatible with the hypothesis that high-order interactions play a role in shaping the dynamics of neural networks, and that they should be taken into account when computing the representational capacity of neural populations.
publishDate 2009
dc.date.none.fl_str_mv 2009
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/10915/160254
url http://sedici.unlp.edu.ar/handle/10915/160254
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/issn/1471-2962
info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2009.0082
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
3297–3310
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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