Direct causality measures unravel complex networks of cardiovascular dynamics and their modifications with postural stress.

This study provides a novel network perspective on the spontaneous short-term regulatory mechanisms underlying cardiovascular and cardiorespiratory interactions during different physiological states. The direct causality measure of conditional transfer entropy was estimated employing linear model-based and nonlinear model-free approaches and applied to the network of beat-to-beat heart period, arterial pressure, respiration, and arterial compliance variability series assessed in thirty-nine young healthy subjects monitored in the supine resting state and during orthostatic stress. The network analysis retrieved well-known regulatory mechanisms significant in most of the subjects, such as the tilt-induced decreased respiratory sinus arrhythmia and increased baroreflex, and uncovered less explored interaction pathways involving compliance. Specifically, we found a decreased effect of heart period and arterial pressure on compliance, as well as a stronger causal influence from compliance to arterial pressure and a decreased influence of compliance on respiration. The joint use of model-based and model-free approaches allowed us to infer the linear or nonlinear nature of these interactions. Our study advocates the main role played by arterial compliance into the intricate hank of cardiovascular interactions, and documents the need to employ direct causality measures to infer the many complex mechanisms generating short-term cardiovascular oscillations.