Weak convergence of stochastic neuronal models
Weak convergence of stochastic neuronal models
复制标题
随机神经元模型的弱收敛
DOI：
10.1007/978-3-642-46599-4_9
复制
发表时间：
1985
期刊：
影响因子：
--
通讯作者：
R. Wolpert
中科院分区：
文献类型：
--
作者：
G. Kallianpur;R. Wolpert
自从1952年Hodgkin和Huxley的里程碑式的论文以来，神经元膜的电行为和离子电流的作用已经被研究和理解。十多年前，随着实验性膜片钳技术的发展，证实了表现出随机行为的离子门的存在，并且这些离子门的性质和结构在1984年由Nodaet al. [1984]的完整氨基酸链，包括钠门控通道的电器官ofelectrophorus electricus.尽管所有这些实验的进展，尽管广泛的兴趣，以获得更好地了解的行为，个别神经元和系统的神经元，有很少成功的努力，发展随机数学模型，能够反映和帮助预测神经元的活动。我们研究的一个目标是开发此类模型，以阐明分散在单个孤立神经元表面膜上的数千个门控分子的微动力学行为与宏观动力学行为之间的联系，该神经元受到一系列兴奋性和抑制性脉冲的影响。同一神经元在产生和传播动作电位和锋电位序列时的行为。我们不解决相互连接的神经元网络如何表现的有趣问题。
The electrical behavior of neuronal membranes and the role of ion currents have been studied and understood since the landmark 1952 papers of Hodgkin and Huxley. The existence of ionic gates exhibiting stochastic behavior was confirmed over ten years ago with the development of the experimental patch-clamp technique, and the nature and structure of those ionic gates was illuminated dramatically in 1984 with the publication by Nodaet al.[1984] of the complete amino acid chain comprising the sodium gating channel for the electric organ ofelectrophorus electricus.Despite all this experimental progress, and despite the wide interest in gaining a better understanding of the behavior of individual neurons and of systems of neurons, there has been little success in the efforts to develop stochastic mathematical models capable of reflecting and helping to predict neuronal activity. It is a goal of our research to develop such models in order to illuminate the connection between the microkinetic behavior of thousands of gating molecules scattered over the surface membrane of a single isolated neuron subject to a stream of excitatory and inhibitory impulses, and the macrokinetic behavior of that same neuron in generating and propagating action potentials and spike trains. We do not address the interesting questions of how networks of interconnected neurons behave.