论文标题
泄漏的集成和开火神经元输出流的力矩函数
Moment-generating function of output stream of leaky integrate-and-fire neuron
论文作者
论文摘要
神经元在其在其刺激过程中通过形成随机泊松过程的输入脉冲流的统计量进行了研究。泄漏的集成和传火神经元被认为是神经元模型。找到了输出串联间隔持续时间的概率分布函数的新表示。基于它，明确计算了概率分布的力矩函数。根据柯蒂斯定理，后者完全决定了分布本身。特别是，显式表达式来自所有顺序的时刻矩产生的函数。第一刻与之前发现的时刻相吻合。通过直接对具有特定物理参数的神经元的随机动力学进行直接建模，对第二和第三矩的公式进行了数值检查。
The statistics of the output activity of a neuron during its stimulation by the stream of input impulses that forms the stochastic Poisson process is studied. The leaky integrate-and-fire neuron is considered as a neuron model. A new representation of the probability distribution function of the output interspike interval durations is found. Based on it, the moment-generating function of the probability distribution is calculated explicitly. The latter, according to Curtiss theorem, completely determines the distribution itself. In particular, explicit expressions are derived from the moment-generating function for the moments of all orders. The first moment coincides with the one found earlier. Formulas for the second and third moments have been checked numerically by direct modeling of the stochastic dynamics of a neuron with specific physical parameters.
