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首页> 外文期刊>Advanced Functional Materials >Synaptic Suppression Triplet-STDP Learning Rule Realized in Second-Order Memristors
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Synaptic Suppression Triplet-STDP Learning Rule Realized in Second-Order Memristors

机译：二阶忆阻器中突触抑制三联体-STDP学习规则的实现

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摘要

The synaptic weight modification depends not only on interval of the pre-/postspike pairs according to spike-timing dependent plasticity (classical pair-STDP), but also on the timing of the preceding spike (triplet-STDP). Triplet-STDP reflects the unavoidable interaction of spike pairs in natural spike trains through the short-term suppression effect of preceding spikes. Second-order memristors with one state variable possessing short-term dynamics work in a way similar to the biological system. In this work, the suppression triplet-STDP learning rule is faithfully demonstrated by experiments and simulations using second-order memristors. Furthermore, a leaky-integrate-and-fire (LIF) neuron is simulated using a circuit constructed with second-order memristors. Taking the advantage of the LIF neuron, various neuromimetic dynamic processes, including local graded potential leaking out, postsynaptic impulse generation and backpropagation, and synaptic weight modification according to the suppression triplet-STDP rule, are realized. The realized weight-dependent pair- and triplet-STDP rules are clearly in line with findings in biology. The physically realized triplet-STDP rule is powerful in developing direction and speed selectivity for complex pattern recognition and tracking tasks. These scalable artificial synapses and neurons realized in second-order memristors can intrinsically capture the neuromimetic dynamic processes; they are the promising building blocks for constructing brain-inspired computation systems.
机译：突触权重的改变不仅取决于尖峰时间依赖的可塑性（经典对-STDP），还取决于尖峰前/后尖峰对的间隔，还取决于前一个尖峰的时间（三联峰-STDP）。三重态-STDP通过前面的峰值的短期抑制作用反映了自然峰值序列中不可避免的峰值对相互作用。具有一个状态变量且具有短期动力学的二阶忆阻器的工作方式类似于生物系统。在这项工作中，通过使用二阶忆阻器进行的实验和仿真，忠实地演示了抑制三重态STDP学习规则。此外，使用由二阶忆阻器构成的电路来模拟泄漏积分和发射（LIF）神经元。利用LIF神经元的优势，实现了多种神经模拟动力学过程，包括局部分级的电位泄漏，突触后冲动生成和反向传播以及根据抑制三联体STDP规则进行的突触权重修改。已实现的重量依赖性成对和三联体-STDP规则显然与生物学发现相符。物理实现的三重态STDP规则在开发方向和速度选择性方面非常强大，可用于复杂的模式识别和跟踪任务。这些可扩展的人工突触和在二阶忆阻器中实现的神经元可以内在地捕获拟神经动力学过程。它们是构建受大脑启发的计算系统的有前途的构建基块。

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  • 来源
    《Advanced Functional Materials》 |2018年第5期|1704455.1-1704455.10|共10页
  • 作者

    Yang Rui; Huang He-Ming; Hong Qing-Hui; Yin Xue-Bing; Tan Zheng-Hua; Shi Tuo; Zhou Ya-Xiong; Miao Xiang-Shui; Wang Xiao-Ping; Mi Shao-Bo; Jia Chun-Lin; Guo Xin;

  • 作者单位

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, WNLO, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, WNLO, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China;

    Xi An Jiao Tong Univ, State Key Lab Mech Behav Mat, Xian 710049, Shaanxi, Peoples R China;

    Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Shaanxi, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Mat Sci & Engn, Wuhan 430074, Hubei, Peoples R China;

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  • 正文语种 eng
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  • 关键词

    leaky-integrate-and-fire neurons; second-order memristors; synapses; triplet-STDP;

    机译：泄漏整合并发射神经元;二阶忆阻器;突触;三胞胎STDP;

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