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| Content Provider | PubMed Central |
|---|---|
| Author | Montalto, Alessandro Faes, Luca Daniele, Marinazzo |
| Editor | Baumert, Mathias |
| Copyright Year | 2014 |
| 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. |
| Related Links | http://dx.doi.org/10.1371/journal.pone.0109462 |
| Starting Page | 109462 |
| File Format | |
| ISSN | 19326203 |
| e-ISSN | 19326203 |
| Journal | PLoS ONE |
| Issue Number | 10 |
| Volume Number | 9 |
| Language | English |
| Publisher | Public Library of Science |
| Publisher Date | 2014-10-01 |
| Access Restriction | Open |
| Rights Holder | Public Library of Science |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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