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

Luca Faes, Daniele Marinazzo, Luca Faes, Alessandro Montalto

Risultato della ricerca: Article

61 Citazioni (Scopus)

Abstract

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.
Lingua originaleEnglish
Numero di pagine13
RivistaPLoS One
Volume9
Stato di pubblicazionePublished - 2014

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All Science Journal Classification (ASJC) codes

  • General
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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