Ben-Tal Alona, Shamailov Sophie S, Paton Julian F R
Institute of Natural and Mathematical Sciences, Massey University, Albany, Private Bag 102-904, North Shore Mail Centre, Auckland, New Zealand.
Institute of Natural and Mathematical Sciences, Massey University, Albany, Private Bag 102-904, North Shore Mail Centre, Auckland, New Zealand.
Math Biosci. 2014 Sep;255:71-82. doi: 10.1016/j.mbs.2014.06.015. Epub 2014 Jul 6.
A minimal model for the neural control of heart rate (HR) has been developed with the aim of better understanding respiratory sinus arrhythmia (RSA)--a modulation of HR at the frequency of breathing. This model consists of two differential equations and is integrated into a previously-published model of gas exchange. The heart period is assumed to be affected primarily by the parasympathetic signal, with the sympathetic signal taken as a parameter in the model. We include the baroreflex, mechanical stretch-receptor feedback from the lungs, and central modulation of the cardiac vagal tone by the respiratory drive. Our model mimics a range of experimental observations and provides several new insights. Most notably, the model mimics the growth in the amplitude of RSA with decreasing respiratory frequency up to 7 breaths per minute (for humans). Our model then mimics the decrease in the amplitude of RSA at frequencies below 7 breaths per minute and predicts that this decrease is due to the baroreflex (we show this both numerically and analytically with a linear baroreflex). Another new prediction of the model is that the gating of the baroreflex leads to the dependency of RSA on mean vagal tone. The new model was also used to test two previously-suggested hypotheses regarding the physiological function of RSA and supports the hypothesis that RSA minimizes the work done by the heart while maintaining physiological levels of arterial CO2. These and other new insights the model provides extend our understanding of the integrative nature of vagal control of the heart.
为了更好地理解呼吸性窦性心律不齐（RSA）——一种在呼吸频率下对心率（HR）的调节，已经开发了一种心率神经控制的最小模型。该模型由两个微分方程组成，并被整合到一个先前发表的气体交换模型中。假定心脏周期主要受副交感神经信号的影响，交感神经信号在模型中作为一个参数。我们纳入了压力反射、来自肺部的机械牵张感受器反馈以及呼吸驱动对心脏迷走神经张力的中枢调节。我们的模型模拟了一系列实验观察结果，并提供了一些新的见解。最值得注意的是，该模型模拟了在呼吸频率降至每分钟7次呼吸（对于人类）时RSA振幅的增加。然后我们的模型模拟了在呼吸频率低于每分钟7次呼吸时RSA振幅的降低，并预测这种降低是由于压力反射（我们通过线性压力反射在数值和分析上都证明了这一点）。该模型的另一个新预测是压力反射的门控导致RSA对平均迷走神经张力的依赖性。这个新模型还被用于检验两个先前提出的关于RSA生理功能的假设，并支持RSA在维持动脉血二氧化碳生理水平的同时使心脏做功最小化的假设。该模型提供的这些以及其他新见解扩展了我们对心脏迷走神经控制整合性质的理解。
