Cutts Catherine S, Eglen Stephen J
Cambridge Computational Biology Institute Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, United Kingdom
Cambridge Computational Biology Institute Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, United Kingdom.
J Neurosci. 2014 Oct 22;34(43):14288-303. doi: 10.1523/JNEUROSCI.2767-14.2014.
Correlations in neuronal spike times are thought to be key to processing in many neural systems. Many measures have been proposed to summarize these correlations and of these the correlation index is widely used and is the standard in studies of spontaneous retinal activity. We show that this measure has two undesirable properties: it is unbounded above and confounded by firing rate. We list properties needed for a measure to fairly quantify and compare correlations and we propose a novel measure of correlation-the spike time tiling coefficient. This coefficient, the correlation index, and 33 other measures of correlation of spike times are blindly tested for the required properties on synthetic and experimental data. Based on this, we propose a measure (the spike time tiling coefficient) to replace the correlation index. To demonstrate the benefits of this measure, we reanalyze data from seven key studies, which previously used the correlation index to investigate the nature of spontaneous activity. We reanalyze data from β2(KO) and β2(TG) mutants, mutants lacking connexin isoforms, and also the age-dependent changes in wild-type and β2(KO) correlations. Reanalysis of the data using the proposed measure can significantly change the conclusions. It leads to better quantification of correlations and therefore better inference from the data. We hope that the proposed measure will have wide applications, and will help clarify the role of activity in retinotopic map formation.
神经元放电时间的相关性被认为是许多神经系统处理过程的关键。人们提出了许多方法来总结这些相关性,其中相关性指数被广泛使用,并且是自发视网膜活动研究中的标准方法。我们表明,这种方法具有两个不良特性:它没有上限并且会受到放电率的混淆。我们列出了一种方法为了公平地量化和比较相关性所需具备的特性,并提出了一种新的相关性度量方法——放电时间平铺系数。在合成数据和实验数据上,对该系数、相关性指数以及其他33种放电时间相关性度量方法进行了所需特性的盲测。基于此,我们提出了一种方法(放电时间平铺系数)来取代相关性指数。为了证明这种方法的优势,我们重新分析了七项关键研究的数据,这些研究之前使用相关性指数来研究自发活动的性质。我们重新分析了β2(KO)和β2(TG)突变体(缺乏连接蛋白亚型的突变体)的数据,以及野生型和β2(KO)相关性的年龄依赖性变化。使用所提出的方法重新分析数据会显著改变结论。它能够更好地量化相关性,从而从数据中得出更好的推断。我们希望所提出的方法将有广泛的应用,并有助于阐明活动在视网膜拓扑图形成中的作用。