Clamann H P
Biophys J. 1969 Oct;9(10):1233-51. doi: 10.1016/S0006-3495(69)86448-9.
A statistical analysis of the firing pattern of single motor units in the human brachial biceps muscle is presented. Single motor unit spike trains are recorded and analyzed. The statistical treatment of these spike trains is as stochastic point processes, the theory of which is briefly discussed. Evidence is presented that motor unit spike trains may be modelled by a renewal process with an underlying gaussian probability density. Statistical independence of successive interspike intervals is shown using scatter diagrams; the hypothesis of a gaussian distribution is accepted at the 99th percentile confidence limit, chi-square test, in 90% of the units tested. A functional relationship between the mean and standard deviation is shown and discussed; its implications in obtaining sample size are presented in an appendix.The results of higher order analysis in the form of autocorrelograms and grouped interval histograms are presented. Grouped interval histograms are discussed in the context of motor unit data, and used to confirm the hypothesis that a stable probability density function does not represent a good model of the data at this level of analysis.
本文对人体肱二头肌中单个运动单位的放电模式进行了统计分析。记录并分析了单个运动单位的尖峰序列。这些尖峰序列的统计处理是作为随机点过程进行的,文中简要讨论了其理论。有证据表明,运动单位尖峰序列可以用具有潜在高斯概率密度的更新过程来建模。使用散点图显示了连续峰间间隔的统计独立性;在90%的测试单位中,在第99百分位数置信限、卡方检验下,高斯分布的假设被接受。展示并讨论了均值与标准差之间的函数关系;附录中介绍了其在确定样本量方面的意义。以自相关图和分组间隔直方图形式呈现了高阶分析的结果。在运动单位数据的背景下讨论了分组间隔直方图,并用于确认这样一个假设:在这个分析层面,稳定的概率密度函数并不能很好地代表数据模型。