Tixier Eliott, Lombardi Damiano, Rodriguez Blanca, Gerbeau Jean-Frédéric
Sorbonne Universités, UPMC Université Paris 6, UMR 7598 LJLL, 75005 Paris, France.
Inria Paris, 75012 Paris, France.
J R Soc Interface. 2017 Aug;14(133). doi: 10.1098/rsif.2017.0238.
The variability observed in action potential (AP) cardiomyocyte measurements is the consequence of many different sources of randomness. Often ignored, this variability may be studied to gain insight into the cell ionic properties. In this paper, we focus on the study of ionic channel conductances and describe a methodology to estimate their probability density function (PDF) from AP recordings. The method relies on the matching of observable statistical moments and on the maximum entropy principle. We present four case studies using synthetic and sets of experimental AP measurements from human and canine cardiomyocytes. In each case, the proposed methodology is applied to infer the PDF of key conductances from the exhibited variability. The estimated PDFs are discussed and, when possible, compared to the true distributions. We conclude that it is possible to extract relevant information from the variability in AP measurements and discuss the limitations and possible implications of the proposed approach.
在动作电位（AP）心肌细胞测量中观察到的变异性是许多不同随机源的结果。这种变异性常常被忽视，但可以通过研究它来深入了解细胞的离子特性。在本文中，我们专注于离子通道电导的研究，并描述了一种从AP记录中估计其概率密度函数（PDF）的方法。该方法依赖于可观测统计矩的匹配以及最大熵原理。我们展示了四个案例研究，使用了来自人类和犬类心肌细胞的合成数据和实验AP测量数据集。在每个案例中，所提出的方法都被用于从所呈现的变异性中推断关键电导的PDF。我们对估计出的PDF进行了讨论，并在可能的情况下与真实分布进行了比较。我们得出结论，从AP测量的变异性中提取相关信息是可能的，并讨论了所提出方法的局限性和可能的影响。
