神经元重复活动的随机模型。
A stochastic model of the repetitive activity of neurons.
出版信息
Biophys J. 1966 Jan;6(1):53-69. doi: 10.1016/S0006-3495(66)86639-0.
Abstract
A recurrent model of the repetitive firing of neurons responding to stimuli of long duration is given. The model assumes a deterministic threshold potential and a membrane potential which is composed of both deterministic and random components. The model accurately reproduces interval statistics obtained from different neurons discharging repetitively over a wide range of discharge rates. It is shown that the model has three important parameters; the time course of threshold recovery following a discharge, the variance of the random component, and the level of excitatory drive. The model is extended, by the use of hyperpolarizing afterpotentials, to include negative correlation between successive interspike intervals.
摘要
给出了一个对长时间刺激反应的神经元重复发射的重现模型。该模型假设了一个确定性的阈值电位和一个由确定性和随机分量组成的膜电位。该模型准确地再现了从不同神经元在广泛的放电率范围内重复放电中获得的间隔统计。结果表明，该模型有三个重要参数：放电后阈值恢复的时间过程、随机分量的方差和兴奋性驱动的水平。通过使用超极化后电位，该模型得到了扩展，包括了连续的尖峰间隔之间的负相关。
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