Bienenstock–Cooper–Munro Learning Rule Realized in Polysaccharide-Gated Synaptic Transistors with Tunable Threshold,ACS Applied Materials & Interfaces

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Bienenstock–Cooper–Munro Learning Rule Realized in Polysaccharide-Gated Synaptic Transistors with Tunable Threshold
ACS Applied Materials & Interfaces ( IF 8.3 ) Pub Date : 2020-10-26 , DOI: 10.1021/acsami.0c14325
Jianmiao Guo ₁ , Yanghui Liu ₁ , Yingtao Li ₁ , Fangzhou Li ₁ , Feng Huang ₁

Affiliation

With reference to the organization of the human brain nervous system, a hardware-based approach that builds massively parallel neuromorphic circuits is of great significance to neuromorphic computing. The Bienenstock–Cooper–Munro (BCM) learning rule, which describes that the synaptic weight modulation exhibits frequency-dependent and tunable frequency threshold characteristics, is more compatible with the working principle of neuromorphic computing systems than spike-timing-dependent plasticity. Therefore, it is interesting to simulate the BCM learning rule on solid-state synaptic devices. Here, we have prepared λ-carrageenan (λ-car) electrolyte-gated oxide synaptic transistors, which exhibit good transistor performances, including a low subthreshold swing of 125 mV/dec, an on/off ratio larger than 10⁶, and a mobility of 9.5 cm² V^–1 s^–1. By modulating the initial channel current and spike frequency, the simulation of the BCM rule was successfully realized. The competitive relationship between the drift of protons under an electric field and the spontaneous diffusion of protons can explain this mechanism. The proposed λ-car-gated synaptic transistor has a great significance to neuromorphic computing.

中文翻译：

具有可变阈值的多糖门控突触晶体管中实现的Bienenstock–Cooper–Munro学习规则

关于人脑神经系统的组织，建立大规模并行的神经形态电路的基于硬件的方法对神经形态计算具有重要意义。Bienenstock–Cooper–Munro（BCM）学习规则，该规则描述了突触权重调制具有频率依赖性和可调频率阈值特征，与神经形态计算系统的工作原理兼容，而不是依赖于峰值定时的可塑性。因此，有趣的是在固态突触设备上模拟BCM学习规则。在这里，我们准备了λ-角叉菜胶（λ-car）电解质门控氧化物突触晶体管，该晶体管具有良好的晶体管性能，包括亚阈值摆幅低至125 mV / dec，开/关比大于10 ⁶，迁移率为9.5 cm ² V ^–1 s ^–1。通过调制初始通道电流和尖峰频率，成功实现了BCM规则的仿真。电场作用下质子的漂移与质子的自发扩散之间的竞争关系可以解释这种机理。提出的λ-car-gated突触晶体管对神经形态计算具有重要意义。

更新日期：2020-11-04

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