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First Passage Time Distribution for Spiking Neuron with Delayed Excitatory Feedback

机译:具有延迟兴奋性反馈的脉冲神经元的首次通过时间分布

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摘要

A class of spiking neuronal models with threshold 2 is considered. It is defined by a set of conditions typical for basic threshold-type models, such as the leaky integrate-and-fire (LIF) or the binding neuron model, and also for some artificial neurons. A neuron is stimulated with a Poisson stream of excitatory impulses. Each output impulse is conveyed through the feedback line to the neuron input after finite delay Delta. This impulse is identical to those delivered from the input stream. We have obtained a general relation allowing calculating exactly the probability density function (PDF) p(t) for distribution of the first passage time of crossing the threshold, which is the distribution of output interspike intervals (ISI) values for this neuron. The calculation is based on known PDF p(0)(t) for that same neuron without feedback, intensity of the input stream lambda and properties of the feedback line. Also, we derive exact relation for calculating the moments of p(t) based on known moments of p(0)(t).
机译:考虑了一类阈值为 2 的脉冲神经元模型。它由一组基本阈值型模型的典型条件定义,例如泄漏的整合和触发 (LIF) 或结合神经元模型,以及一些人工神经元。神经元受到兴奋性冲动的泊松流的刺激。每个输出脉冲在有限延迟 Delta 后通过反馈线传递到神经元输入。此脉冲与从输入流传递的脉冲相同。我们已经获得了一个一般关系,可以精确计算概率密度函数 (PDF) p(t) 的分布,用于跨越阈值的第一次通过时间的分布,即该神经元的输出尖峰间间隔 (ISI) 值的分布。计算基于没有反馈的同一神经元的已知 PDF p(0)(t)、输入流 lambda 的强度和反馈线的属性。此外,我们根据 p(0)(t) 的已知矩推导出计算 p(t) 矩的精确关系。

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