While studying complex systems, one of the fundamental questions is to identify causal relationships (i.e., which system drives which) between relevant subsystems. In this paper, we focus on information-theoretic approaches for causality detection by means of directionality index based on mutual information estimation. We briefly review the current methods for mutual information estimation from the point of view of their consistency. We also present some arguments from recent literature, supporting the usefulness of the information-theoretic tools for causality detection.

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