Izhikevich E M
The Neurosciences Institute, San Diego, CA 92121, USA.
Neural Netw. 2001 Jul-Sep;14(6-7):883-94. doi: 10.1016/s0893-6080(01)00078-8.
We suggest a simple spiking model-resonate-and-fire neuron, which is similar to the integrate-and-fire neuron except that the state variable is complex. The model provides geometric illustrations to many interesting phenomena occurring in biological neurons having subthreshold damped oscillations of membrane potential. For example, such neurons prefer a certain resonant frequency of the input that is nearly equal to their eigenfrequency, they can be excited or inhibited by a doublet (two pulses) depending on its interspike interval, and they can fire in response to an inhibitory input. All these properties could be observed in Hodgkin-Huxley-type models. We use the resonate-and-fire model to illustrate possible sensitivity of biological neurons to the fine temporal structure of the input spike train. Being an analogue of the integrate-and-fire model, the resonate-and-fire model is computationally efficient and suitable for simulations of large networks of spiking neurons.
我们提出一种简单的脉冲发放模型——共振并发放神经元，它与积分发放神经元相似，只是状态变量是复数。该模型为生物神经元中膜电位存在阈下阻尼振荡时出现的许多有趣现象提供了几何图示。例如，这类神经元偏好与它们的本征频率近似相等的特定输入共振频率，根据其脉冲间隔，它们可被双脉冲（两个脉冲）兴奋或抑制，并且它们可对抑制性输入做出发放反应。所有这些特性在霍奇金-赫胥黎型模型中都能观察到。我们使用共振并发放模型来说明生物神经元对输入脉冲序列精细时间结构可能的敏感性。作为积分发放模型的一种类似物，共振并发放模型计算效率高，适用于对大型脉冲发放神经元网络进行模拟。
