Quantifying information transfer and mediation along causal pathways in complex systems
Jakob Runge

TL;DR
This paper develops new information-theoretic measures to quantify and interpret causal information transfer pathways in complex systems, accounting for indirect influences and intermediate processes, with applications to climatology.
Contribution
It introduces novel measures for assessing information transfer along causal paths and the contribution of intermediate processes, based on a multivariate causal network reconstruction.
Findings
New measures quantify information transfer along causal pathways.
Application to climatology illustrates disentangling atmospheric flow pathways.
Framework relates information transfer to underlying dynamics.
Abstract
Measures of information transfer have become a popular approach to analyze interactions in complex systems such as the Earth or the human brain from measured time series. Recent work has focused on causal definitions of information transfer excluding effects of common drivers and indirect influences. While the former clearly constitutes a spurious causality, the aim of the present article is to develop measures quantifying different notions of the strength of information transfer along indirect causal paths, based on first reconstructing the multivariate causal network (\emph{Tigramite} approach). Another class of novel measures quantifies to what extent different intermediate processes on causal paths contribute to an interaction mechanism to determine pathways of causal information transfer. A rigorous mathematical framework allows for a clear information-theoretic interpretation that…
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