Stochastic-Shielding Approximation of Markov Chains and its Application to Efficiently Simulate Random Ion-Channel Gating
Stochastic-Shielding Approximation of Markov Chains and its Application to Efficiently Simulate Random Ion-Channel Gating
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DOI：
10.1103/physrevlett.109.118101
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发表时间：
2012-09-11
影响因子：
8.6
通讯作者：
Galan, Roberto F.
中科院分区：
文献类型：
--
作者：
Schmandt, Nicolaus T.;Galan, Roberto F.
马尔可夫链提供了自然界中众多随机过程的现实模型。我们证明，在任何马尔可夫链中，当且仅当 A 和 B 直接连接时，状态 A 中的占用数的变化与状态 B 中的占用数的变化相关。这意味着，如果我们只对状态 A 感兴趣，如果状态 B 不直接与 A 连接，则 B 的波动可以用它们的平均值代替，从而大大缩短计算时间。我们在理论上和神经元随机离子通道门控模拟中展示了我们的近似的准确性和有效性。
Markov chains provide realistic models of numerous stochastic processes in nature. We demonstrate that in any Markov chain, the change in occupation number in state A is correlated to the change in occupation number in state B if and only if A and B are directly connected. This implies that if we are only interested in state A, fluctuations in B may be replaced with their mean if state B is not directly connected to A, which shortens computing time considerably. We show the accuracy and efficacy of our approximation theoretically and in simulations of stochastic ion-channel gating in neurons.