Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation.
Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation.
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DOI：
10.3389/fncom.2013.00058
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发表时间：
2013
影响因子：
3.2
通讯作者：
Stricker C
中科院分区：
文献类型：
--
作者：
McDonnell MD;Mohan A;Stricker C
已知突触前动作电位 (AP) 到达皮质突触后神经递质囊泡的释放是一个随机过程，释放囊泡的可用性也是如此。已知这些过程还取决于 AP 到达的最近历史，这可以用囊泡释放的时变概率来描述。这种突触动力学的数学模型通常仅基于每个突触前 AP 释放的囊泡的平均数量，因为如果假设有足够多的囊泡位点，则方差很小。然而，最近的研究表明，不同位点的差异对于神经元和网络动力学来说可能很重要，这表明使用确实产生试验间变异性的模拟来研究短期可塑性的潜在重要性。因此，在本文中，我们研究了几种著名的随机可用性和释放概念模型。我们明确说明这些模型描述的随机变量，并提出有效的算法，以在软件或硬件中准确实现这些随机变量的随机模拟。我们的结果得到了数学分析和伪代码算法的陈述的补充。
The release of neurotransmitter vesicles after arrival of a pre-synaptic action potential (AP) at cortical synapses is known to be a stochastic process, as is the availability of vesicles for release. These processes are known to also depend on the recent history of AP arrivals, and this can be described in terms of time-varying probabilities of vesicle release. Mathematical models of such synaptic dynamics frequently are based only on the mean number of vesicles released by each pre-synaptic AP, since if it is assumed there are sufficiently many vesicle sites, then variance is small. However, it has been shown recently that variance across sites can be significant for neuron and network dynamics, and this suggests the potential importance of studying short-term plasticity using simulations that do generate trial-to-trial variability. Therefore, in this paper we study several well-known conceptual models for stochastic availability and release. We state explicitly the random variables that these models describe and propose efficient algorithms for accurately implementing stochastic simulations of these random variables in software or hardware. Our results are complemented by mathematical analysis and statement of pseudo-code algorithms.
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