Amjad A M, Halliday D M, Rosenberg J R, Conway B A
Division of Neuroscience and Biomedical Systems, Institute of Biomedical and Life Sciences, University of Glasgow, UK.
J Neurosci Methods. 1997 Apr 25;73(1):69-79. doi: 10.1016/s0165-0270(96)02214-5.
Recently there has been an increase in the use of spectral methods for the analysis of experimental data. These analytical methods allow the study of interactions between simultaneously recorded signals and are particularly suited to the study of systems displaying rhythmic behaviour. A useful parameter in this context is the coherence function which provides a bounded measure of linear association between two signals. In this report we introduce two new techniques for dealing with an arbitrary number of independent coherence estimates. The first technique provides a test to compare the coherence estimates for statistically significant differences. The second allows the original coherence estimates to be combined, or 'pooled' into a single representative estimate. These two measures, taken together, provide a powerful tool for characterising and summarising the correlations within data sets. Applications of the techniques are illustrated by analysing the interactions between single motor unit discharges and finger tremor, and between pairs of motor unit discharges in human subjects.
最近,用于实验数据分析的谱方法的使用有所增加。这些分析方法允许研究同时记录的信号之间的相互作用,特别适合于研究表现出节律性行为的系统。在这种情况下,一个有用的参数是相干函数,它提供了两个信号之间线性关联的有界度量。在本报告中,我们介绍了两种处理任意数量独立相干估计的新技术。第一种技术提供了一种检验,用于比较相干估计的统计显著差异。第二种技术允许将原始的相干估计合并,或“汇总”为一个单一的代表性估计。这两种方法结合在一起,为表征和总结数据集中的相关性提供了一个强大的工具。通过分析人类受试者单个运动单位放电与手指震颤之间以及成对运动单位放电之间的相互作用,说明了这些技术的应用。