Blümel Marcus, Guschlbauer Christoph, Daun-Gruhn Silvia, Hooper Scott L, Büschges Ansgar
Zoologisches Institut, Universität zu Köln, Cologne, Germany.
Biol Cybern. 2012 Nov;106(10):559-71. doi: 10.1007/s00422-012-0530-6. Epub 2012 Nov 7.
Models built using mean data can represent only a very small percentage, or none, of the population being modeled, and produce different activity than any member of it. Overcoming this "averaging" pitfall requires measuring, in single individuals in single experiments, all of the system's defining characteristics. We have developed protocols that allow all the parameters in the curves used in typical Hill-type models (passive and active force-length, series elasticity, force-activation, force-velocity) to be determined from experiments on individual stick insect muscles (Blümel et al. 2012a). A requirement for means to not well represent the population is that the population shows large variation in its defining characteristics. We therefore used these protocols to measure extensor muscle defining parameters in multiple animals. Across-animal variability in these parameters can be very large, ranging from 1.3- to 17-fold. This large variation is consistent with earlier data in which extensor muscle responses to identical motor neuron driving showed large animal-to-animal variability (Hooper et al. 2006), and suggests accurate modeling of extensor muscles requires modeling individual-by-individual. These complete characterizations of individual muscles also allowed us to test for parameter correlations. Two parameter pairs significantly co-varied, suggesting that a simpler model could as well reproduce muscle response.
使用平均数据构建的模型仅能代表被建模群体中非常小的比例,甚至可能一个个体都代表不了,并且其产生的活动与该群体中的任何个体都不同。要克服这种“平均化”的缺陷,需要在单个实验中的单个个体上测量系统的所有定义特征。我们已经开发出了方案,能够从对单个竹节虫肌肉的实验中确定典型希尔型模型(被动和主动力-长度、串联弹性、力-激活、力-速度)所使用曲线中的所有参数(布吕梅尔等人,2012a)。均值不能很好地代表群体的一个必要条件是群体在其定义特征上表现出很大的变异性。因此,我们使用这些方案来测量多只动物伸肌的定义参数。这些参数在不同动物之间的变异性可能非常大,范围从1.3倍到17倍。这种巨大的变异性与早期的数据一致,在早期数据中,伸肌对相同运动神经元驱动的反应在不同动物之间表现出很大的变异性(胡珀等人,2006),这表明对伸肌进行准确建模需要逐个个体进行建模。对单个肌肉的这些完整表征也使我们能够测试参数之间的相关性。有两对参数显著共同变化,这表明一个更简单的模型也能够重现肌肉反应。