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脉冲神经元模型:积分发放单元与弛豫振荡器。

Models for Spiking Neurons: Integrate-and-Fire Units and Relaxation Oscillators.

作者信息

Crisp Kevin

机构信息

Biology Department, St. Olaf College, Northfield, MN 55057.

出版信息

J Undergrad Neurosci Educ. 2019 Jun 30;17(2):E7-E12. eCollection 2019 Spring.

Abstract

Relaxation oscillators are nonlinear electronic circuits that produce a repetitive non-sinusoidal waveform when sufficient voltage is applied. In this fashion, they are reminiscent of integrate-and-fire neuron models, except that they also include components with hysteresis, and thus require no threshold rule to determine when an impulse has occurred or to return the voltage to its reset value. Here, I discuss the pros and cons of teaching elementary neurophysiology using first-order linear integrate-and-fire neurons versus relaxation oscillator circuits. I suggest that the shortcomings of both types of models are useful in order to foster a critical understanding of the neurophysiology underlying the firing dynamics of biological neurons.

摘要

张弛振荡器是一种非线性电子电路,当施加足够电压时会产生重复的非正弦波形。以这种方式,它们让人联想到积分发放神经元模型,只是它们还包括具有滞后现象的组件,因此不需要阈值规则来确定何时发生冲动或将电压恢复到其重置值。在这里,我讨论了使用一阶线性积分发放神经元与张弛振荡器电路教授基础神经生理学的利弊。我认为这两种模型的缺点都有助于培养对生物神经元放电动力学背后神经生理学的批判性理解。

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