title: MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
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.
authors.affiliation: Data Analysis Department, Ghent University, Ghent, Belgium.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Montalto
authors.affiliation: BIOtech, Department of Industrial Engineering, University of Trento, and IRCS-PAT FBK, Trento, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Faes
authors.affiliation: Data Analysis Department, Ghent University, Ghent, Belgium.
authors.forename: Daniele
authors.initials: D
authors.lastname: Marinazzo
mesh_terms: D000465:Algorithms; D002318:Cardiovascular Diseases / Q000503:physiopathology; D003198:Computer Simulation; D004569:Electroencephalography; D019277:Entropy; D004827:Epilepsy / Q000503:physiopathology; D006801:Humans; D008962:Models, Theoretical; D012372:ROC Curve; D012984:Software