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模型突触的随机条件作用诱导的长时程增强和抑制

Long-term potentiation and depression induced by a stochastic conditioning of a model synapse.

作者信息

Migliore M, Lansky P

机构信息

Institute of Advanced Diagnostic Methodologies, National Research Council, Palermo, Italy.

出版信息

Biophys J. 1999 Sep;77(3):1234-43. doi: 10.1016/S0006-3495(99)76975-4.

Abstract

Protracted presynaptic activity can induce long-term potentiation (LTP) or long-term depression (LTD) of the synaptic strength. However, virtually all the experiments testing how LTP and LTD depend on the conditioning input are carried out with trains of stimuli at constant frequencies, whereas neurons in vivo most likely experience a stochastic variation of interstimulus intervals. We used a computational model of synaptic transmission to test if and to what extent the stochastic fluctuations of an input signal could alter the probability to change the state of a synapse. We found that, even if the mean stimulation frequency was maintained constant, the probability to induce LTD and LTP could be a function of the temporal variation of the input activity. This mechanism, which depends only on the statistical properties of the input and not on the onset of additional biochemical mechanisms, is not usually considered in the experiments, but it could have an important role to determine the amount of LTP/LTD induction in vivo. In response to a change in the distribution of the interstimulus intervals, as measured by the coefficient of variation, a synapse could be easily adapted to inputs that might require immediate attention, with a shift of the input thresholds required to elicit LTD or LTP, which are restored to their initial conditions as soon as the input pattern returns to the original temporal distribution.

摘要

长时间的突触前活动可诱导突触强度的长时程增强(LTP)或长时程抑制(LTD)。然而,几乎所有测试LTP和LTD如何依赖于条件输入的实验都是在恒定频率的刺激序列下进行的,而体内的神经元很可能经历刺激间隔的随机变化。我们使用突触传递的计算模型来测试输入信号的随机波动是否以及在多大程度上会改变突触状态改变的概率。我们发现,即使平均刺激频率保持恒定,诱导LTD和LTP的概率也可能是输入活动时间变化的函数。这种机制仅取决于输入的统计特性,而不依赖于其他生化机制的启动,在实验中通常未被考虑,但它可能在决定体内LTP/LTD诱导量方面发挥重要作用。响应于刺激间隔分布的变化(以变异系数衡量),突触可以很容易地适应可能需要立即关注的输入,引发LTD或LTP所需的输入阈值会发生偏移,一旦输入模式恢复到原始时间分布,这些阈值就会恢复到初始条件。

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