Patla A E, Calvert T W, Stein R B
Am J Physiol. 1985 Apr;248(4 Pt 2):R484-94. doi: 10.1152/ajpregu.1985.248.4.R484.
This paper presents an analytic model of a limb pattern generator that can produce complex muscle activation patterns such as those shown to control the limbs of cats. The limb pattern generator is considered to have a tonic input and six outputs; this provides for flexion and extension of representative muscles for each of the three joints of the limb. The pattern generator functions as a community of labile synthesized relaxation oscillators that alters its output in response to input. This model was studied using electromyographic data from an experiment conducted on an acute postmammillary cat preparation. The results suggest that the limb pattern generator can be represented as three subsystems: an oscillator that produces the fundamental frequency of the output in response to the tonic signal, nonlinear shaping functions that mold the oscillator output into the basic complex pattern, and appropriate weighting functions that generate the muscle activity pattern from basic waveforms. The model can account for speed changes in locomotion with a relatively smooth change of system parameters. The pattern generator model is generative, amenable to simulation studies, and can be realized by a neural network.
本文提出了一种肢体模式发生器的分析模型,该模型能够产生复杂的肌肉激活模式,如那些被证明可控制猫科动物肢体的模式。肢体模式发生器被认为具有一个紧张性输入和六个输出;这为肢体三个关节中每个关节的代表性肌肉的屈伸提供了条件。模式发生器作为一个不稳定的合成松弛振荡器群落发挥作用,它根据输入改变其输出。该模型是利用对急性乳头后猫制备物进行的一项实验所获得的肌电图数据进行研究的。结果表明,肢体模式发生器可表示为三个子系统:一个响应紧张性信号产生输出基频的振荡器、将振荡器输出塑造为基本复杂模式的非线性整形函数,以及从基本波形生成肌肉活动模式的适当加权函数。该模型能够通过系统参数的相对平滑变化来解释运动中的速度变化。模式发生器模型具有生成性,适合进行模拟研究,并且可以通过神经网络实现。