An artificial spiking afferent nerve based on Mott memristors for neurorobotics

Xumeng Zhang, Ye Zhuo, Qing Luo, Zuheng Wu, Rivu Midya, Zhongrui Wang, Wenhao Song, Rui Wang, Navnidhi K. Upadhyay, Yilin Fang, Fatemeh Kiani, Mingyi Rao, Yang Yang, Qiangfei Xia, Qi Liu (), Ming Liu () and J. Joshua Yang ()
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Xumeng Zhang: University of Massachusetts
Ye Zhuo: University of Massachusetts
Qing Luo: Institute of Microelectronics of the Chinese Academy of Sciences
Zuheng Wu: Institute of Microelectronics of the Chinese Academy of Sciences
Rivu Midya: University of Massachusetts
Zhongrui Wang: University of Massachusetts
Wenhao Song: University of Massachusetts
Rui Wang: University of Massachusetts
Navnidhi K. Upadhyay: University of Massachusetts
Yilin Fang: Institute of Microelectronics of the Chinese Academy of Sciences
Fatemeh Kiani: University of Massachusetts
Mingyi Rao: University of Massachusetts
Yang Yang: Institute of Microelectronics of the Chinese Academy of Sciences
Qiangfei Xia: University of Massachusetts
Qi Liu: Institute of Microelectronics of the Chinese Academy of Sciences
Ming Liu: Institute of Microelectronics of the Chinese Academy of Sciences
J. Joshua Yang: University of Massachusetts

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Neuromorphic computing based on spikes offers great potential in highly efficient computing paradigms. Recently, several hardware implementations of spiking neural networks based on traditional complementary metal-oxide semiconductor technology or memristors have been developed. However, an interface (called an afferent nerve in biology) with the environment, which converts the analog signal from sensors into spikes in spiking neural networks, is yet to be demonstrated. Here we propose and experimentally demonstrate an artificial spiking afferent nerve based on highly reliable NbOx Mott memristors for the first time. The spiking frequency of the afferent nerve is proportional to the stimuli intensity before encountering noxiously high stimuli, and then starts to reduce the spiking frequency at an inflection point. Using this afferent nerve, we further build a power-free spiking mechanoreceptor system with a passive piezoelectric device as the tactile sensor. The experimental results indicate that our afferent nerve is promising for constructing self-aware neurorobotics in the future.

Date: 2020
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DOI: 10.1038/s41467-019-13827-6

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