• Am. J. Physiol. Regul. Integr. Comp. Physiol. · Dec 2003

    Directionality of coupling of physiological subsystems: age-related changes of cardiorespiratory interaction during different sleep stages in babies.

    • Ralf Mrowka, Laura Cimponeriu, Andreas Patzak, and Michael G Rosenblum.
    • Johannes-Müller Institut für Physiologie, Humboldt-Universität zu Berlin, Tucholskystrasse 2, D-10117 Berlin, Germany. mrowka@rz.hu-berlin.de
    • Am. J. Physiol. Regul. Integr. Comp. Physiol. 2003 Dec 1;285(6):R1395-401.

    AbstractActivity of many physiological subsystems has a well-expressed rhythmic character. Often, a dependency between physiological rhythms is established due to interaction between the corresponding subsystems. Traditional methods of data analysis allow one to quantify the strength of interaction but not the causal interrelation that is indispensable for understanding the mechanisms of interaction. Here we present a recently developed method for quantification of coupling direction and apply it to an important problem. Namely, we study the mutual influence of respiratory and cardiovascular rhythms in healthy newborns within the first 6 mo of life in quiet and active sleep. We find an age-related change of the coupling direction: the interaction is nearly symmetric during the first days and becomes practically unidirectional (from respiration to heart rhythm) at the age of 6 mo. Next, we show that the direction of interaction is mainly determined by respiratory frequency. If the latter is less than approximately 0.6 Hz, the interaction occurs dominantly from respiration to heart. With higher respiratory frequencies that only occur at very young ages, the dominating direction is less pronounced or even abolished. The observed dependencies are not related to sleep stage, suggesting that the coupling direction is determined by system-inherent dynamical processes, rather than by functional modulations. The directional analysis may be applied to other interacting narrow band oscillatory systems, e.g., in the central nervous system. Thus it is an important step forward in revealing and understanding causal mechanisms of interactions.

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