Bio‐Inspired P‐type TeSeO <sub>x</sub> Synaptic Transistor Based on Multispectral Sensing for Neuromorphic Visual Multilevel Nociceptor

The development of neuromorphic color vision has significant research implications in the fields of machine vision and artificial intelligence. By mimicking the processing mechanisms of energy-efficient biological visual systems, it offers a unique potential for real-time color environment perception and dynamic adaptability. This paper reports on a multispectral color sensing synaptic device based on a novel p-type TeSeO<sub>x</sub> transistor, applied to a neuromorphic visual multilevel nociceptor. Due to the intrinsic properties of TeSeO<sub>x</sub>, its narrow bandgap allows for multi-wavelength (405, 532, 655 nm) response, and its oxide semiconductor-based persistent photoconductivity converts optical signals into stored electrical signals, successfully emulating key synaptic characteristics such as excitatory postsynaptic current (EPSC), multi-pulse facilitation, and the transition from short-term to long-term memory. Additionally, it simulates learning, forgetting, and relearning behaviors, as well as image memory under tricolor light. Finally, using optical signals as a pain stimulus, the fundamental functions of a nociceptor are realized, including "threshold," "non-adaptation," "relaxation," and "nociceptive sensitization". More importantly, by using tricolor light, multilevel pain perception is acheived. These results have the potential to advance fields such as autonomous driving, machine vision, and intelligent alert systems.

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Publication Details

Journal
Small Methods
Published
2024-11-24
DOI
https://doi.org/10.1002/smtd.202401543
Citations
6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.25

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article

Bio‐Inspired P‐type TeSeO x Synaptic Transistor Based on Multispectral Sensing for Neuromorphic Visual Multilevel Nociceptor

Shancheng Yan, Sixian Li, Feng Zhang, Yong Xu et al.
6 citations
Small Methods
Advanced Memory and Neural Computing
1.25
article

Bio‐Inspired P‐type TeSeO x Synaptic Transistor Based on Multispectral Sensing for Neuromorphic Visual Multilevel Nociceptor

Shancheng Yan, Sixian Li, Feng Zhang, Yong Xu, Huabin Sun, Ao Liu, Xiang Wan, Zhihao Yu, Li Zhu, Chee Leong Tan
article en
6 citations

Abstract

The development of neuromorphic color vision has significant research implications in the fields of machine vision and artificial intelligence. By mimicking the processing mechanisms of energy-efficient biological visual systems, it offers a unique potential for real-time color environment perception and dynamic adaptability. This paper reports on a multispectral color sensing synaptic device based on a novel p-type TeSeO<sub>x</sub> transistor, applied to a neuromorphic visual multilevel nociceptor. Due to the intrinsic properties of TeSeO<sub>x</sub>, its narrow bandgap allows for multi-wavelength (405, 532, 655 nm) response, and its oxide semiconductor-based persistent photoconductivity converts optical signals into stored electrical signals, successfully emulating key synaptic characteristics such as excitatory postsynaptic current (EPSC), multi-pulse facilitation, and the transition from short-term to long-term memory. Additionally, it simulates learning, forgetting, and relearning behaviors, as well as image memory under tricolor light. Finally, using optical signals as a pain stimulus, the fundamental functions of a nociceptor are realized, including "threshold," "non-adaptation," "relaxation," and "nociceptive sensitization". More importantly, by using tricolor light, multilevel pain perception is acheived. These results have the potential to advance fields such as autonomous driving, machine vision, and intelligent alert systems.

Small MethodsVol. 9(5)
University of Electronic Science and Technology of China (CN), Nanjing University of Posts and Telecommunications (CN), Guangdong Greater Bay Area Institute of Integrated Circuit and System
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, Natural Science Research of Jiangsu Higher Education Institutions of China
Affordable and clean energy
Openalex Percentile: Top 20%
Advanced Memory and Neural Computing
1.25
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