0000000000146081
AUTHOR
A. Montalto
Information decomposition of short-term cardiovascular and cardiorespiratory variability
We present an entropy decomposition strategy aimed at quantifying how the predictive information (PI) about heart rate (HR) variability is dynamically stored in HR and is transferred to HR from arterial pressure (AP) and respiration (RS) variability according to synergistic or redundant cooperation. The PI is expressed as the sum of the self entropy (SE) of HR plus the transfer entropy (TE) from RS,AP to HR, quantifying respectively the information stored in the cardiac system and transferred to the cardiac system to the vascular and respiratory systems. The information transfer is further decomposed as the sum of the (unconditioned) TE from RS to HR plus the TE from SP to HR conditioned to…
Comparing model-free and model-based transfer entropy estimators in cardiovascular variability
Information flow between heart period (T), systolic pressure (S) and respiration (R) variability in a head-up tilt (HUT) protocol is assessed by transfer entropy (TE). Two estimates of TE are compared: the model-based (MB) approach using linear regression under the Gaussian assumption, and the model-free (MF) approach combining binning estimates of entropy and non-uniform delay embedding. The approaches were applied to 300-beats series of T, S, R measured in the supine (su) and upright (up) positions during HUT. Both MB and MF approaches detected a unidirectional information transfer from R to T and from R to S, and a significant decrease of the TE from R to T, as well as a significant incr…