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基于现场可编程门阵列的霍奇金-赫胥黎模型神经元动作电位数值模拟功能的硬件实现

[Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

作者信息

Wang Jinlong, Lu Mai, Hu Yanwen, Chen Xiaoqiang, Pan Qiangqiang

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2015 Dec;32(6):1302-9.

Abstract

Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new research ideas to clinical treatment of spinal cord injury, bionics and artificial intelligence. Based on the HH model neuron and the DSP Builder technology, in the present study, a single HH model neuron hardware implementation was completed in Field Programmable Gate Array (FPGA). The neuron implemented in FPGA was stimulated by different types of current, the action potential response characteristics were analyzed, and the correlation coefficient between numerical simulation result and hardware implementation result were calculated. The results showed that neuronal action potential response of FPGA was highly consistent with numerical simulation result. This work lays the foundation for hardware implementation of neural network.

摘要

神经元是生物神经系统的基本单位。霍奇金-赫胥黎(HH)模型是在神经元电生理特性描述方面最逼真的神经元模型之一。神经元的硬件实现可为脊髓损伤的临床治疗、仿生学和人工智能提供新的研究思路。基于HH模型神经元和DSP Builder技术,在本研究中,在现场可编程门阵列(FPGA)中完成了单个HH模型神经元的硬件实现。对在FPGA中实现的神经元施加不同类型的电流刺激,分析动作电位响应特性,并计算数值模拟结果与硬件实现结果之间的相关系数。结果表明,FPGA的神经元动作电位响应与数值模拟结果高度一致。这项工作为神经网络的硬件实现奠定了基础。

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