MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological network...

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Autores principales:	Alessandro Montalto, Luca Faes, Daniele Marinazzo
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/30a376d8c198486fae1d775ab6a1ad4d
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spelling	oai:doaj.org-article:30a376d8c198486fae1d775ab6a1ad4d2021-11-25T05:56:40ZMuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.1932-620310.1371/journal.pone.0109462https://doaj.org/article/30a376d8c198486fae1d775ab6a1ad4d2014-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0109462https://doaj.org/toc/1932-6203A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different approaches to evaluate transfer entropy, some of them already proposed, some novel, and present their implementation in a freeware MATLAB toolbox. Applications to simulated and real data are presented.Alessandro MontaltoLuca FaesDaniele MarinazzoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 10, p e109462 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Alessandro Montalto Luca Faes Daniele Marinazzo MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
description	A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different approaches to evaluate transfer entropy, some of them already proposed, some novel, and present their implementation in a freeware MATLAB toolbox. Applications to simulated and real data are presented.
format	article
author	Alessandro Montalto Luca Faes Daniele Marinazzo
author_facet	Alessandro Montalto Luca Faes Daniele Marinazzo
author_sort	Alessandro Montalto
title	MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
title_short	MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
title_full	MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
title_fullStr	MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
title_full_unstemmed	MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
title_sort	mute: a matlab toolbox to compare established and novel estimators of the multivariate transfer entropy.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/30a376d8c198486fae1d775ab6a1ad4d
work_keys_str_mv	AT alessandromontalto muteamatlabtoolboxtocompareestablishedandnovelestimatorsofthemultivariatetransferentropy AT lucafaes muteamatlabtoolboxtocompareestablishedandnovelestimatorsofthemultivariatetransferentropy AT danielemarinazzo muteamatlabtoolboxtocompareestablishedandnovelestimatorsofthemultivariatetransferentropy
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MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

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