Tchaptchet Aubin, Postnova Svetlana, Finke Christian, Schneider Horst, Huber Martin T, Braun Hans A
Neurodynamics Group, Institute of Physiology, University of Marburg, Deutschhausstr. 2, D-35037 Marburg, Germany.
Brain Res. 2013 Nov 6;1536:159-67. doi: 10.1016/j.brainres.2013.06.029. Epub 2013 Jul 31.
A mechanism-based, Hodgkin-Huxley-type modeling approach is proposed that allows connecting the key parameters of experimental voltage-/patch-clamp data directly to the major control values of the model. The objective of this paper is to facilitate the use of mathematical modeling in supplement to electrophysiological recordings. Typical recordings from current-clamp, whole-cell voltage-clamp, and single-channel patch-clamp experiments are illustrated by means of a simplified computer model designed for life science education. These examples demonstrate that the "rate constants", on which the original Hodgkin-Huxley equations are built up, are difficult, in most experiments even impossible, to extract from experimental data. As the combination of the two exponential rate constants leads to sigmoid activation curves, they can be replaced by sigmoid voltage dependencies, mostly presented in form of Boltzmann functions. Conversely, connecting whole-cell and single-channel patch-clamp simulations, the Boltzmann functions, can be related to exponentially voltage dependent probability factors of ion channel transition rates. The thereby introduced small variability of the activation values suggests that the power functions of the activation variables in the current equations can be neglected. Eliminating the rate constants and the power functions can be physiologically justified and makes the model easier to handle, especially in context with experimental data. Further possibilities of dimension reduction as well as model extensions are discussed. This article is part of a Special Issue entitled Neural Coding 2012.
本文提出了一种基于机制的霍奇金-赫胥黎型建模方法,该方法能够将实验电压/膜片钳数据的关键参数直接与模型的主要控制值联系起来。本文的目的是促进数学建模在电生理记录补充中的应用。通过一个为生命科学教育设计的简化计算机模型,展示了电流钳、全细胞电压钳和单通道膜片钳实验的典型记录。这些例子表明,构建原始霍奇金-赫胥黎方程的“速率常数”在大多数实验中很难甚至无法从实验数据中提取。由于两个指数速率常数的组合会产生S形激活曲线,它们可以被S形电压依赖性所取代,大多以玻尔兹曼函数的形式呈现。相反,连接全细胞和单通道膜片钳模拟时,玻尔兹曼函数可以与离子通道转换速率的指数电压依赖性概率因子相关。由此引入的激活值的小变异性表明,电流方程中激活变量的幂函数可以忽略不计。消除速率常数和幂函数在生理上是合理的,并且使模型更易于处理,特别是在与实验数据相关的情况下。还讨论了进一步降维和模型扩展的可能性。本文是名为《神经编码2012》特刊的一部分。