On directed information theory and Granger causality graphs

Details On directed information theory and Granger causality graphs On directed information theory and Granger causality graphs

2010-02-07

arxiv.org/abs/1002.1446v1

J. Comput. Neurosci. (2010), 30:7-16

Computer Science

Information Theory

accepted for publications, Journal of Computational Neuroscience

Scientific paper

10.1007/s10827-010-0231-x

Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.

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