Princeton University, Princeton, NJ 08544, USA.
J Exp Biol. 2010 Feb 15;213(4):643-50. doi: 10.1242/jeb.037598.
A model is developed to predict the force generated by active skeletal muscle when subjected to imposed patterns of lengthening and shortening, such as those that occur during normal movements. The model is based on data from isolated lamprey muscle and can predict the forces developed during swimming. The model consists of a set of ordinary differential equations, which are solved numerically. The model's first part is a simplified description of the kinetics of Ca(2+) release from sarcoplasmic reticulum and binding to muscle protein filaments, in response to neural activation. The second part is based on A. V. Hill's mechanical model of muscle, consisting of elastic and contractile elements in series, the latter obeying known physiological properties. The parameters of the model are determined by fitting the appropriate mathematical solutions to data recorded from isolated lamprey muscle activated under conditions of constant length or rate of change of length. The model is then used to predict the forces developed under conditions of applied sinusoidal length changes, and the results compared with corresponding data. The most significant advance of this model is the incorporation of work-dependent deactivation, whereby a muscle that has been shortening under load generates less force after the shortening ceases than otherwise expected. In addition, the stiffness in this model is not constant but increases with increasing activation. The model yields a closer prediction to data than has been obtained before, and can thus prove an important component of investigations of the neural-mechanical-environmental interactions that occur during natural movements.
建立了一个模型,用于预测在受到强制拉长和缩短模式(如在正常运动中发生的那些)作用下主动骨骼肌产生的力。该模型基于来自分离的七鳃鳗肌肉的数据,可以预测游泳过程中产生的力。该模型由一组常微分方程组成,通过数值求解。模型的第一部分是对神经激活时肌浆网中 Ca(2+)释放和与肌肉蛋白丝结合的动力学的简化描述。第二部分基于 A. V. Hill 的肌肉力学模型,由串联的弹性和收缩元件组成,后者遵循已知的生理特性。模型的参数通过将适当的数学解拟合到在恒长或长度变化率条件下激活的分离的七鳃鳗肌肉记录的数据来确定。然后,该模型用于预测在施加正弦长度变化条件下产生的力,并将结果与相应的数据进行比较。该模型的最重要进展是纳入了依赖于工作的失活,由此,在负载下缩短的肌肉在缩短停止后产生的力比预期的要小。此外,该模型中的刚度不是恒定的,而是随着激活的增加而增加。该模型产生的数据预测比以前更接近,因此可以证明是研究在自然运动过程中发生的神经力学环境相互作用的重要组成部分。