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MuTE: A MATLAB Toolbox to Compare Established and Novel Estimators of the Multivariate Transfer Entropy

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  • Alessandro Montalto
  • Luca Faes
  • Daniele Marinazzo

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.

Suggested Citation

  • Alessandro Montalto & Luca Faes & Daniele Marinazzo, 2014. "MuTE: A MATLAB Toolbox to Compare Established and Novel Estimators of the Multivariate Transfer Entropy," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.
    • Handle: RePEc:plo:pone00:0109462
    DOI: 10.1371/journal.pone.0109462
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    Cited by:

    1. M. Lavanga & O. De Wel & A. Caicedo & K. Jansen & A. Dereymaeker & G. Naulaers & S. Van Huffel, 2017. "Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation," Complexity, Hindawi, vol. 2017, pages 1-13, October.
    2. Katerina Rigana & Ernst C. Wit & Samantha Cook, 2024. "Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk," Papers 2402.06032, arXiv.org.
    3. Jian Zhang, 2018. "Low-dimensional approximation searching strategy for transfer entropy from non-uniform embedding," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-24, March.
    4. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    5. Wu, Zhe & Zhang, Qiang & Cheng, Lifeng & Hou, Shuyong & Tan, Shengyue, 2020. "The VMTES: Application to the structural health monitoring and diagnosis of rotating machines," Renewable Energy, Elsevier, vol. 162(C), pages 2380-2396.

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