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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/160254
Ver los metadatos del registro completo
id |
SEDICI_68d5d363654ffc1451e3e5883e0ce42f |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/160254 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
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 |
_version_ |
1844616290475442176 |
score |
13.070432 |