6533b85cfe1ef96bd12bc942
RESEARCH PRODUCT
MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.
Luca FaesDaniele MarinazzoAlessandro Montaltosubject
Multivariate statisticsInformation transferTheoretical computer scienceComputer scienceEntropyInformation TheorySocial SciencesCAUSALITYMedicine (all); Biochemistry Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all)BioinformaticsMedicine and Health SciencesEntropy (energy dispersal)MultidisciplinaryEntropy (statistical thermodynamics)Medicine (all)QSoftware DevelopmentREstimatorSoftware EngineeringElectroencephalographyCausalityNeurologyCardiovascular DiseasesProbability distributionMedicineAlgorithmsResearch ArticleComputer ModelingComputer and Information SciencesScienceCardiologyProbability density functionEntropy (classical thermodynamics)Artificial IntelligenceLinear regressionEntropy (information theory)HumansComputer SimulationEntropy (arrow of time)Conditional entropyBiochemistry Genetics and Molecular Biology (all)EpilepsyBiology and Life SciencesModels TheoreticalMODELNonlinear systemAgricultural and Biological Sciences (all)ROC CurveINFORMATION-TRANSFERSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCognitive ScienceTransfer entropySoftwareEntropy (order and disorder)Neurosciencedescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-10-14 | PLoS ONE |