 In the context of information dynamics, SE, TE, CE and CSE were used to analyze the temporal evolution of coupled systems. Theoretical properties of these measures were discussed, including their existence and meaning. An approach was developed for computing information dynamics using the linear Gaussian approximation. These measures were then applied to cardiorespiratory dynamics data collected from healthy subjects, under different experimental conditions. By combining the measures, it was possible to identify the causal effects associated with the observed dynamics and to interpret how they changed, with varying experimental conditions. This article was authored by Luca Faiz, Alberto Porta, and Gian Domenico Nallo.