Application to Life Sciences

Abstract

The proposed theory and methods are applied for the analysis of biological oscillatory systems affected by external dynamical influences. The main investigation is performed on physiological measurements under conditions where the breathing frequency is varied linearly, thus introducing a deterministic non-autonomous timevariation into the oscillatory system. Methods able to track time-varying characteristics are applied to signals from the cardiovascular, and the sympathetic neural systems. The time-varying breathing process significantly affected the functioning and regulation of several physiological mechanisms, demonstrating a clear imprint of the particular form of externally induced time-variation. Specifically, low frequencies of breathing provoked more information flow, interfering with the coordination and increasing the coupling strength between the oscillatory processes. Statistical analyses are performed to identify significant relationships, and the proposed inferential method is applied. The technique demonstrates that cardiorespiratory coordination depends on, and to a large extent is regulated by, respiratory dynamics. Time-varying respiration caused synchronization transitions between different orders. An additional complexity is that the coupling functions are also identified as being time-varying processes. A technique based on the synchrosqueezed wavelet transform shows how the instantaneous phase can be extracted from complex mixed-mode signals with timevarying characteristics. The latter procedure is demonstrated on several physiological signals of this kind. A dynamical characterization for the reproducibility of blood flow is shown to be more appropriate than conventional time-averaged analysis. This also implies that care must be taken when external perturbations are made consecutively.