An FPGA-based Implementation Method for Quadratic Spiking Neuron Model

Xianghong Lin, Hang Lu, Xiaomei Pi, Xiangwen Wang
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引用次数: 1

Abstract

In the innovative neural prostheses, the biological cell assemblies of the biological nervous system can be replaced by artificial organs, which makes the idea of dynamically interface biological neurons even more urgent. To mimic and investigate the activity of biological neural networks, many different architectures and technologies in the field of neuromorphic have been developed at present. When structuring simple neuron models, researchers use Field programmable gate arrays (FPGAs) to obtain better accuracy and real-time performance. This paper uses FPGAs to achieve the circuit design of the neuron model, such that based on the biologically plausible the quadratic spiking neuron model, can simulate the neuron spiking behaviors of thalamus neurons and hippocampal CA1 pyramidal neurons. After the FPGA hardware architecture of the neuron model is designed and implemented, this model can better simulate the spiking behaviors observed in biological neurons.
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基于fpga的二次脉冲神经元模型实现方法
在创新的神经假体中,生物神经系统的生物细胞组件可以被人工器官取代,这使得动态界面生物神经元的想法变得更加迫切。为了模拟和研究生物神经网络的活动,目前在神经形态领域发展了许多不同的体系结构和技术。在构建简单的神经元模型时,研究人员使用现场可编程门阵列(fpga)来获得更好的准确性和实时性。本文利用fpga实现神经元模型的电路设计,使基于生物学上合理的二次尖峰神经元模型,可以模拟丘脑神经元和海马CA1锥体神经元的神经元尖峰行为。在设计并实现神经元模型的FPGA硬件架构后,该模型可以更好地模拟生物神经元中观察到的尖峰行为。
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