Information-theoretic methods for studying population codes

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...

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Detalles Bibliográficos
Autores principales: Ince, Robin A.A., Senatore, Riccardo, Arabzadeh, Ehsan, Montani, Fernando Fabián, Diamond, Mathew E., Panzeri, Stefano
Formato: Articulo
Lenguaje:Inglés
Publicado: 2010
Materias:
Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/160253
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-160253
record_format dspace
spelling I19-R120-10915-1602532023-11-16T20:06:34Z http://sedici.unlp.edu.ar/handle/10915/160253 Information-theoretic methods for studying population codes Ince, Robin A.A. Senatore, Riccardo Arabzadeh, Ehsan Montani, Fernando Fabián Diamond, Mathew E. Panzeri, Stefano 2010 2023-11-16T16:20:02Z en Física Mutual information Sampling bias Population coding Somatosensory cortex 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 Articulo Articulo http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 713-727
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
spellingShingle Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
Ince, Robin A.A.
Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
Information-theoretic methods for studying population codes
topic_facet Física
Mutual information
Sampling bias
Population coding
Somatosensory cortex
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.
format Articulo
Articulo
author Ince, Robin A.A.
Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
author_facet Ince, Robin A.A.
Senatore, Riccardo
Arabzadeh, Ehsan
Montani, Fernando Fabián
Diamond, Mathew E.
Panzeri, Stefano
author_sort Ince, Robin A.A.
title Information-theoretic methods for studying population codes
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
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/160253
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AT montanifernandofabian informationtheoreticmethodsforstudyingpopulationcodes
AT diamondmathewe informationtheoreticmethodsforstudyingpopulationcodes
AT panzeristefano informationtheoreticmethodsforstudyingpopulationcodes
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