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

机译:MuTE:MATLAB工具箱,用于比较多元传递熵的既有估计和新颖估计

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摘要

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.
机译:生理学家和神经科学家面临的挑战是绘制他们在不同规模研究的系统组件之间的信息传递图,以便从记录的动力学分析中获得有关结构和功能的重要知识。生理网络的组成部分通常以非线性方式并通过通常不完全了解的机制相互作用。因此,比较安全的是,用于分析这些交互的选择方法不依赖于任何模型或对数据及其交互性质的假设。传递熵已经成为量化有向动力学相互作用的有力工具。在本文中,我们比较了评估传输熵的不同方法,其中一些已经提出,一些新颖,并在免费的MATLAB工具箱中展示了它们的实现。介绍了模拟和真实数据的应用。

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