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SIMULINK MODEL OF SPIKING NEURAL OSCILLATOR

机译:尖峰神经振荡器的SIMULINK模型

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摘要

A Simulink model of a spiking neural network of two neurons that works as a neural oscillator is presented. Each neuron is based upon Izhikevich Spiking Neuron Model. Average Response Model is used to model various aspects of synaptic transmissions. The parameters in the mathematical differential equation describing each neuron are set such that they exhibit a regular spiking pattern of cortical neurons. The duty cycle and frequency of oscillations of our oscillator are quite flexible and are tuned by varying one or more of a few parameters, for example, changing the nature of synapses. The presence of very few parameters reduces the complexity of simulation and allows this neural oscillator model to be easily implemented in myriad applications that involve sustained rhythmic patterns. An initial spike of stimulus is enough to drive this oscillator.
机译:提出了两个神经元的尖峰神经网络的Simulink模型,该模型充当神经振荡器。每个神经元都基于Izhikevich尖峰神经元模型。平均响应模型用于对突触传递的各个方面进行建模。设置描述每个神经元的数学微分方程中的参数,以使其表现出皮质神经元的规则尖峰图形。我们振荡器的占空比和振荡频率非常灵活,可以通过更改一些参数中的一个或多个来进行调整,例如,更改突触的性质。很少参数的存在降低了仿真的复杂性,并使该神经振荡器模型可以轻松地在涉及持续节奏模式的多种应用中实施。刺激的初始尖峰足以驱动该振荡器。

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