Cooperation among Heart Rate, Respiration and Locomotion Rhythms and Homeodynamics---Experimental and Theoretical Study

内稳态动力学是生物体内稳态的一个延伸概念，与后者一样，它与包括自主神经系统在内的中枢神经系统对生物体内部状态的控制有关，生物体内的内稳态是指生物体的节律性活动，如心跳呼吸甚至是运动活动都可以是反映或影响内环境控制的可观察变量。基于这些可观察变量的内环境动力学控制（测量数据）。上述节律活动具有称为动态稳定性的共同性质，这是非线性动力系统的特征。即，系统状态总是随时间变化，但变化的状态对于外部扰动是稳定的。为了理解与稳态控制相关的基础系统的基本性质，有必要识别/建模底层系统，然后考虑功能角色 ...更多信息 沿着这一思路，我们做了以下沿着研究：1.动态稳定性的定量分析我们分析了两个与动态稳定性和稳态动力学相关的案例：A：动态稳定性的估计和运动节律的建模; B：心律不稳定性和心律失常转变的仿真研究，阐明了动态稳定性的不稳定性与心脏生理的关系.从时间序列数据中辨识和建模未知非线性系统我们开发了从时间序列数据中估计未知非线性动力系统的实用方法，很自然地假设潜在的非线性动力系统由几个可以取常值的参数来参数化，但是在长时间范围内是变化的。取决于这些参数值，系统可以表现出定性上不同的动态我们的方法可以用来估计模型参数化的几个参数，可以在测量过程中改变。该方法可以适用于模型的心率变异性/控制由于自主神经活动。少

Homeodynamics is an extended concept of the homeostasis of living organisms.As in the latter, it is associated to the control of the inner state of the living organisms by the central nervous system including the autonomic nervous system.Rhythmic activities such as heart beats, respiration and even locomotor activity may be observable variables which reflect or influence the homeodynamic control.This study aims understanding basic mechanism of emergence of the homeodynamic control based on these observable variables (measured data).The rhythmic activities mentioned above share the common property referred to as dynamic stability which is the characteristics of nonlinear dynamical systems.That is, the system state always changes in time, but that varied state is stable against external perturbations.To understand the basic properties of the underlying systems associated to the homeodynamic control, it is necessary to identify/model the underlying system and then consider functional role … More of the dynamic stability.We have done the following studies along this line.1. Quantitative analysis of the dynamic stability.We analyzed two cases associated to the dynamic stability and homeodynamics.A : Dynamic stability estimation and then modeling of the locomotion rhythm.B : Simulation study of the instability of the cardiac rhythm and transition to cardiac arrhythmias.The instability of the dynamic stability in relation to cardiac physiology was exemplified.2. Identification and modeling of unknown nonlinear systems from time series data.We developed practical methods to estimate unknown nonlinear dynamical system from time series data.It is natural to assume the underlying nonlinear dynamical system is parametrized by several parameters which may take constant values, but be varied for long time range.The system may exhibit qualitatively different dynamics depending on these parameter values (bifurcations).Our methods can be utilized to estimate the model parametrized by several parameters which may be altered during the measurements.The methods may be applicable to model heart rate variability/control due to autonomic nerve activities. Less