TRENTOOL: a Matlab open source toolbox to analyse information flow in time series data with transfer entropy.
Background: Transfer entropy (TE) is a measure for the detection of directed interactions. Transfer entropy is an information theoretic implementation of Wiener's principle of observational causality. It offers an approach to the detection of neuronal interactions that is free of an explicit model o...
| Publicado en: | BMC Neuroscience Vol. 12; no. 1; pp. 119 - 120 |
|---|---|
| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
2011
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104498065&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104498065 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14712202 1CI8 jtl: BMC Neuroscience issn: 14712202 maglogo: N pubinfo: dt: 2011 vid: 12 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 104498065 104498065 NLM22098775 2011655394 10.1186/1471-2202-12-119 NLM22098775 PMC3287134 104498065 ppf: 119 ppct: 1 formats: tig: atl: TRENTOOL: a Matlab open source toolbox to analyse information flow in time series data with transfer entropy. aug: au: Lindner, Michael Vicente, Raul Priesemann, Viola Wibral, Michael affil: MEG Unit, Brain Imaging Center, Goethe University, Frankfurt, Germany. sug: subj: Information Science Software Algorithms Animal Studies Brain Stem Physiology Causal Attribution Chaos Theory Computer Simulation Data Analysis, Statistical Electroencephalography Statistics and Numerical Data Electroretinography False Positive Results Human Linear Regression Membrane Potentials Physiology Neural Networks (Computer) Physical Stimulation Physics Reproducibility of Results Retina Physiology Statistics Turtles ab: Background: Transfer entropy (TE) is a measure for the detection of directed interactions. Transfer entropy is an information theoretic implementation of Wiener's principle of observational causality. It offers an approach to the detection of neuronal interactions that is free of an explicit model of the interactions. Hence, it offers the power to analyze linear and nonlinear interactions alike. This allows for example the comprehensive analysis of directed interactions in neural networks at various levels of description. Here we present the open-source MATLAB toolbox TRENTOOL that allows the user to handle the considerable complexity of this measure and to validate the obtained results using non-parametrical statistical testing. We demonstrate the use of the toolbox and the performance of the algorithm on simulated data with nonlinear (quadratic) coupling and on local field potentials (LFP) recorded from the retina and the optic tectum of the turtle (Pseudemys scripta elegans) where a neuronal one-way connection is likely present.Results: In simulated data TE detected information flow in the simulated direction reliably with false positives not exceeding the rates expected under the null hypothesis. In the LFP data we found directed interactions from the retina to the tectum, despite the complicated signal transformations between these stages. No false positive interactions in the reverse directions were detected.Conclusions: TRENTOOL is an implementation of transfer entropy and mutual information analysis that aims to support the user in the application of this information theoretic measure. TRENTOOL is implemented as a MATLAB toolbox and available under an open source license (GPL v3). For the use with neural data TRENTOOL seamlessly integrates with the popular FieldTrip toolbox. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|