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由于离子通道中门控的多样性导致的持续性膜交叉相关性。

Persistent membranous cross correlations due to the multiplicity of gates in ion channels.

作者信息

Güler Marifi

机构信息

Department of Computer Engineering, Eastern Mediterranean University, Famagusta, via Mersin-10, Turkey.

出版信息

J Comput Neurosci. 2011 Nov;31(3):713-24. doi: 10.1007/s10827-011-0337-9. Epub 2011 May 17.

DOI:10.1007/s10827-011-0337-9
PMID:21584774
Abstract

Ion channels in excitable cells reveal spontaneous intermittent opening and closing. As the membrane area reduces, this stochasticity enables spontaneous firing and elevates the cell's ability to fire at weaker stimuli. A multiple number of gates are accommodated in each individual ion channel. Here we investigate the possible impact of that gate multiplicity on the cell's function specifically when the membrane area is of limited size. It is shown that a non-trivially persistent correlation then takes place between the transmembrane voltage fluctuations (also between the fluctuations in the gating variables) and the component of open channel fluctuations attributed to the above gate multiplicity. This cross correlation persistency is found to be playing a major augmentative role in the elevation of the cell's excitability and spontaneous firing; without the persistency, the cell would be much less excitable. The cross correlation persistency is also found to enhance spike coherence. The stochastic Hodgkin-Huxley equations, put forward by Fox and Lu, are addressed in the context of their recognized failure to produce accurate enough statistics of spike generation. Our results indicate that the major source of that inaccuracy is the incapability of the stochastic Hodgkin-Huxley description to reflect the above cross correlation persistency.

摘要

可兴奋细胞中的离子通道会出现自发的间歇性开闭。随着膜面积减小,这种随机性会引发自发放电,并提高细胞在较弱刺激下放电的能力。每个单独的离子通道包含多个门控。在此,我们研究这种门控多样性对细胞功能可能产生的影响,特别是当膜面积有限时。结果表明,跨膜电压波动(以及门控变量的波动)与归因于上述门控多样性的开放通道波动分量之间会出现非平凡的持续相关性。这种交叉相关性的持续性在提高细胞兴奋性和自发放电方面起着主要的增强作用;没有这种持续性,细胞的兴奋性会低得多。交叉相关性的持续性还会增强峰电位相干性。福克斯和陆提出的随机霍奇金 - 赫胥黎方程,在其被认为无法产生足够准确的峰电位生成统计数据的背景下进行了探讨。我们的结果表明,这种不准确性的主要来源是随机霍奇金 - 赫胥黎描述无法反映上述交叉相关性的持续性。

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PLoS Comput Biol. 2011 Mar;7(3):e1001102. doi: 10.1371/journal.pcbi.1001102. Epub 2011 Mar 10.
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Comparison of Langevin and Markov channel noise models for neuronal signal generation.用于神经元信号生成的朗之万(Langevin)和马尔可夫(Markov)通道噪声模型的比较
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