Istituto di Cibernetica "E.Caianiello" del CNR, Via Campi Flegrei 34, 80078 Pozzuoli, NA Italy.
Cogn Neurodyn. 2014 Aug;8(4):327-34. doi: 10.1007/s11571-014-9285-1. Epub 2014 Mar 19.
The excitatory synaptic function is subject to a huge amount of researches and fairly all the structural elements of the synapse are investigated to determine their specific contribution to the response. A model of an excitatory (hippocampal) synapse, based on time discretized Langevin equations (time-step = 40 fs), was introduced to describe the Brownian motion of Glutamate molecules (GLUTs) within the synaptic cleft and their binding to postsynaptic receptors. The binding has been computed by the introduction of a binding probability related to the hits of GLUTs on receptor binding sites. This model has been utilized in computer simulations aimed to describe the random dispersion of the synaptic response, evaluated from the dispersion of the peak amplitude of the excitatory post-synaptic current. The results of the simulation, presented here, have been used to find a reliable numerical quantity for the unknown value of the binding probability. Moreover, the same results have shown that the coefficient of variation decreases when the number of postsynaptic receptors increases, all the other parameters of the process being unchanged. Due to its possible relationships with the learning and memory, this last finding seems to furnish an important clue for understanding the basic mechanisms of the brain activity.
兴奋性突触功能受到了大量的研究,相当多的突触结构元素都被研究过,以确定它们对反应的特定贡献。一个基于时间离散化 Langevin 方程(时间步长=40fs)的兴奋性(海马)突触模型被引入,以描述谷氨酸分子(GLUTs)在突触间隙中的布朗运动及其与突触后受体的结合。通过引入与 GLUTs 击中受体结合位点的概率相关的结合概率来计算结合。该模型已用于计算机模拟,旨在描述从兴奋性突触后电流的峰值幅度的离散来评估的突触反应的随机离散。这里呈现的模拟结果被用于找到绑定概率的未知值的可靠数值量。此外,相同的结果表明,当突触后受体的数量增加时,变异系数减小,而过程的所有其他参数保持不变。由于它可能与学习和记忆有关,这一发现似乎为理解大脑活动的基本机制提供了一个重要线索。