This chapter reports some recent developments of information-theoretic concepts applied to the description of coupled dynamical systems, which allow to decompose the entropy of an assigned target system into components reflecting the information stored in the system and the information transferred to it from the other systems, as well as the nature (synergistic or redundant) of the information transferred to the target. The decomposition leads to well-defined measures of information dynamics which in the chapter will be defined theoretically, computed in simulations of linear Gaussian systems and implemented in practice through the application to heart period, arterial pressure and respiratory time series. The application leads to decompose the information carried by heart rate variability into amounts reflecting cardiac dynamics, vascular and respiratory effects on these dynamics, as well as the interaction between cardiovascular and cardiorespiratory effects. The analysis of head-up and head-down tilt test protocols demonstrates the relevance of information decomposition in dissecting cardiovascular control mechanisms and accept or reject physiological hypotheses about their activity.

Faes, L., Nollo, G., Porta, A. (2017). Information decomposition: A tool to dissect cardiovascular and cardiorespiratory complexity. In Complexity and Nonlinearity in Cardiovascular Signals (pp. 87-113). Springer International Publishing [10.1007/978-3-319-58709-7_3].

Information decomposition: A tool to dissect cardiovascular and cardiorespiratory complexity

Faes, Luca;
2017-01-01

Abstract

This chapter reports some recent developments of information-theoretic concepts applied to the description of coupled dynamical systems, which allow to decompose the entropy of an assigned target system into components reflecting the information stored in the system and the information transferred to it from the other systems, as well as the nature (synergistic or redundant) of the information transferred to the target. The decomposition leads to well-defined measures of information dynamics which in the chapter will be defined theoretically, computed in simulations of linear Gaussian systems and implemented in practice through the application to heart period, arterial pressure and respiratory time series. The application leads to decompose the information carried by heart rate variability into amounts reflecting cardiac dynamics, vascular and respiratory effects on these dynamics, as well as the interaction between cardiovascular and cardiorespiratory effects. The analysis of head-up and head-down tilt test protocols demonstrates the relevance of information decomposition in dissecting cardiovascular control mechanisms and accept or reject physiological hypotheses about their activity.
2017
Settore ING-INF/06 - Bioingegneria Elettronica E Informatica
Faes, L., Nollo, G., Porta, A. (2017). Information decomposition: A tool to dissect cardiovascular and cardiorespiratory complexity. In Complexity and Nonlinearity in Cardiovascular Signals (pp. 87-113). Springer International Publishing [10.1007/978-3-319-58709-7_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/273038
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