Abstract:
Mutual Information Rate (MIR) is the primary method for quantifying the dynamical coupling of two processes in a network. However, it can vary substantially in its condit...Show MoreMetadata
Abstract:
Mutual Information Rate (MIR) is the primary method for quantifying the dynamical coupling of two processes in a network. However, it can vary substantially in its conditioned calculation due to high-order dependencies among the system processes. In this work, we develop a methodology that seeks multiplets of variables that maximize or minimize the dynamic coupling. This allows to decompose the maximal MIR into unique, redundant, and synergistic components, quantifying high-order effects relative importance compared to dyadic effects. The proposed approach is employed to analyze the high order interactions of brain-heart crosstalk in healthy individuals.
Published in: 2024 13th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)
Date of Conference: 23-25 October 2024
Date Added to IEEE Xplore: 29 November 2024
ISBN Information: