计算机科学
编码(社会科学)
神经元
石墨烯
晶体管
神经科学
电压
纳米技术
电气工程
材料科学
心理学
数学
工程类
统计
作者
Changjin Wan,Liqiang Zhu,Yanghui Liu,Ping Feng,Zhaoping Liu,Hailiang Cao,Peng Xiao,Yi Shi,Qing Wan
出处
期刊:Cornell University - arXiv
日期:2015-01-01
被引量:2
标识
DOI:10.48550/arxiv.1510.06115
摘要
Neuron is the most important building block in our brain, and information processing in individual neuron involves the transformation of input synaptic spike trains into an appropriate output spike train. Hardware implementation of neuron by individual ionic/electronic hybrid device is of great significance for enhancing our understanding of the brain and solving sensory processing and complex recognition tasks. Here, we provide a proof-of-principle artificial neuron based on a proton conducting graphene oxide (GO) coupled oxide-based electric-double-layer (EDL) transistor with multiple driving inputs and one modulatory input terminal. Paired-pulse facilitation, dendritic integration and orientation tuning were successfully emulated. Additionally, neuronal gain control (arithmetic) in the scheme of rate coding is also experimentally demonstrated. Our results provide a new-concept approach for building brain-inspired cognitive systems.
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