Biological function simulation in neuromorphic devices: from synapse and neuron to behavior

Hui Chen; Huilin Li; Ting Ma; Shuangshuang Han; Qiuping Zhao

doi:10.1080/14686996.2023.2183712

Biological function simulation in neuromorphic devices: from synapse and neuron to behavior

Sci Technol Adv Mater. 2023 Mar 10;24(1):2183712. doi: 10.1080/14686996.2023.2183712. eCollection 2023.

Authors

Hui Chen¹, Huilin Li², Ting Ma², Shuangshuang Han², Qiuping Zhao¹

Affiliations

¹ Heart Center of Henan Provincial People's Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, P. R. China.
² Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China.

Abstract

As the boom of data storage and processing, brain-inspired computing provides an effective approach to solve the current problem. Various emerging materials and devices have been reported to promote the development of neuromorphic computing. Thereinto, the neuromorphic device represented by memristor has attracted extensive research due to its outstanding property to emulate the brain's functions from synaptic plasticity, sensory-memory neurons to some intelligent behaviors of living creatures. Herein, we mainly review the progress of these brain functions mimicked by neuromorphic devices, concentrating on synapse (i.e. various synaptic plasticity trigger by electricity and/or light), neurons (including the various sensory nervous system) and intelligent behaviors (such as conditioned reflex represented by Pavlov's dog experiment). Finally, some challenges and prospects related to neuromorphic devices are presented.

Keywords: Neuromorphic computing; artificial intelligence; memristor; neuron; synapse.

Publication types

Review

Grants and funding

This study was funded by the Natural Science Foundation of China [Grant No. 52002373], Natural Science Foundation for Young Scientists of Henan Province [Grant No. 202300410071], Joint Construction Project of Henan Medical Science and Technology [Gran No. LHGJ20220103], Postdoctoral Research Grant in Henan Province [Grant No. 202101026], and Young Talents Program of Henan University.