神经形态工程学
抑制性突触后电位
兴奋性突触后电位
激发
记忆电阻器
神经元
电压
人工神经元
人工神经网络
计算机科学
物理
电子工程
电气工程
神经科学
工程类
人工智能
生物
作者
Lingxiang Hu,Zong-Xiao Li,Jiale Shao,Peihong Cheng,Jingrui Wang,Athanasios V. Vasilakos,Liqiang Zhang,Yang Chai,Zhizhen Ye,Fei Zhuge
出处
期刊:Nano Letters
[American Chemical Society]
日期:2024-08-14
卷期号:24 (35): 10865-10873
被引量:8
标识
DOI:10.1021/acs.nanolett.4c02470
摘要
Threshold switching (TS) memristors are promising candidates for artificial neurons in neuromorphic systems. However, they often lack biological plausibility, typically functioning solely in an excitation mode. The absence of an inhibitory mode limits neurons' ability to synergistically process both excitatory and inhibitory synaptic signals. To address this limitation, we propose a novel memristive neuron capable of operating in both excitation and inhibition modes. The memristor's threshold voltage can be reversibly tuned using voltages of different polarities because of its bipolar TS behavior, enabling the device to function as an electronically reconfigurable bi-mode neuron. A variety of neuronal activities such as all-or-nothing behavior and tunable firing probability are mimicked under both excitatory and inhibitory stimuli. Furthermore, we develop a self-adaptive neuromorphic vision sensor based on bi-mode neurons, demonstrating effective object recognition in varied lighting conditions. Thus, our bi-mode neuron offers a versatile platform for constructing neuromorphic systems with rich functionality.
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