Information-theoretic methods for studying population codes

Autores
Ince, Robin A.A.; Senatore, Riccardo; Arabzadeh, Ehsan; Montani, Fernando Fabián; Diamond, Mathew E.; Panzeri, Stefano
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains.
Instituto de Física La Plata
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
Materia
Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
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:10915/160253
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Information-theoretic methods for studying population codesInce, Robin A.A.Senatore, RiccardoArabzadeh, EhsanMontani, Fernando FabiánDiamond, Mathew E.Panzeri, StefanoFísicaMutual informationSampling biasPopulation codingSomatosensory cortexPopulation coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains.Instituto de Física La PlataInstituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas2010info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf713-727http://sedici.unlp.edu.ar/handle/10915/160253enginfo:eu-repo/semantics/altIdentifier/issn/0893-6080info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neunet.2010.05.008info: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:UNLP2025-10-22T17:22:53Zoai:sedici.unlp.edu.ar:10915/160253Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:22:53.294SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Information-theoretic methods for studying population codes
title Information-theoretic methods for studying population codes
spellingShingle Information-theoretic methods for studying population codes
Ince, Robin A.A.
Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
title_short Information-theoretic methods for studying population codes
title_full Information-theoretic methods for studying population codes
title_fullStr Information-theoretic methods for studying population codes
title_full_unstemmed Information-theoretic methods for studying population codes
title_sort Information-theoretic methods for studying population codes
dc.creator.none.fl_str_mv Ince, Robin A.A.
Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
author Ince, Robin A.A.
author_facet Ince, Robin A.A.
Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
author_role author
author2 Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
topic Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
dc.description.none.fl_txt_mv Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains.
Instituto de Física La Plata
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
description Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains.
publishDate 2010
dc.date.none.fl_str_mv 2010
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/10915/160253
url http://sedici.unlp.edu.ar/handle/10915/160253
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0893-6080
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neunet.2010.05.008
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
713-727
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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