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细胞神经科学中的随机混合系统

Stochastic Hybrid Systems in Cellular Neuroscience.

作者信息

Bressloff Paul C, Maclaurin James N

机构信息

Department of Mathematics, University of Utah, Salt Lake City, USA.

出版信息

J Math Neurosci. 2018 Aug 22;8(1):12. doi: 10.1186/s13408-018-0067-7.

Abstract

We review recent work on the theory and applications of stochastic hybrid systems in cellular neuroscience. A stochastic hybrid system or piecewise deterministic Markov process involves the coupling between a piecewise deterministic differential equation and a time-homogeneous Markov chain on some discrete space. The latter typically represents some random switching process. We begin by summarizing the basic theory of stochastic hybrid systems, including various approximation schemes in the fast switching (weak noise) limit. In subsequent sections, we consider various applications of stochastic hybrid systems, including stochastic ion channels and membrane voltage fluctuations, stochastic gap junctions and diffusion in randomly switching environments, and intracellular transport in axons and dendrites. Finally, we describe recent work on phase reduction methods for stochastic hybrid limit cycle oscillators.

摘要

我们回顾了随机混合系统在细胞神经科学中的理论与应用方面的近期研究工作。随机混合系统或分段确定性马尔可夫过程涉及一个分段确定性微分方程与某个离散空间上的时间齐次马尔可夫链之间的耦合。后者通常代表某种随机切换过程。我们首先总结随机混合系统的基本理论,包括快速切换(弱噪声)极限下的各种近似方案。在后续章节中,我们考虑随机混合系统的各种应用,包括随机离子通道和膜电压波动、随机间隙连接以及在随机切换环境中的扩散,还有轴突和树突中的细胞内运输。最后,我们描述了随机混合极限环振荡器的相位约化方法的近期研究工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efc8/6104574/9406c7a05051/13408_2018_67_Fig1_HTML.jpg

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