Silicon Modeling of Spiking Neurons With Diverse Dynamic Behaviors
Silicon Modeling of Spiking Neurons With Diverse Dynamic Behaviors
复制标题
具有多种动态行为的尖峰神经元的硅建模
DOI：
10.1109/tcad.2021.3107245
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发表时间：
2021-08
影响因子：
2.9
通讯作者：
Zhitang Song
中科院分区：
文献类型：
--
作者：
Shenglan Ni;Houpeng Chen;Xi Li;Yu Lei;Qian Wang;Yi Lv;Guangming Zhang;Sannian Song;Zhitang Song
Since spiking neural networks (SNNs) can effectively simulate the information processing mechanism of the biological cortex, they are expected to bridge the gap between neuroscience and machine learning. The hardware simulation of large-scale SNNs requires a simple and versatile silicon neuron model framework. In this article, a spiking neuron circuit as the core device of SNNs is presented. The proposed neuron circuit can mimic the dynamics of different types of biological neurons by adjusting the bias voltage. In order to facilitate the implementation of the spiking neuron circuit based on complementary metal-oxide-semiconductor (CMOS) and reduce the overhead of the circuit area, a modified Mihalas–Niebur (MN) mathematical model is adopted. The improved MN model is biologically plausible and can still successfully display all dynamic behaviors observed in biology. The function of the proposed neuron circuit has been verified by the phase diagram analysis method. The simulation results show the designed neuron circuit can successfully replicate 15 of the 20 firing patterns exhibited by the biological cortex, which proves that the neuron can act as a universal spiking neuron in very large-scale integrated circuit (VLSI) neuromorphic networks.
