用于神经形态自我保护的互补忆阻器人工神经

IF 18.5 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Qiaoling Tian, Xiaoning Zhao, Xichen Tang, Ye Tao, Zhongqiang Wang, Xiaoxiao He, Jianbo Cao, Ya Lin, Haiyang Xu, Yichun Liu
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引用次数: 0

摘要

保护性抑制(PI)行为是人类自我保护的关键,通过减少过度刺激的生理唤醒。模仿PI行为的神经形态硬件可以促进生物逼真人工智能领域的进步,但仍有待研究。本文提出了一种特殊设计的互补记忆电阻器,在多孔非晶碳中嵌入有限的Cu,以模拟PI行为。Cu的耗尽产生互补开关行为,与其生物对应物的PI响应有相似之处。将忆阻器、电阻器和各种传感器集成在一起,产生人工感觉传入神经,可以智能地展示PI对压力、光和温度等刺激的响应行为。作为概念验证,通过发送忆阻器的反馈信号,构建人工运动感觉神经(AMSN)来智能刺激麻醉小鼠的坐骨神经进行神经调节。当刺激增加时,肌肉的过度劳损被成功抑制,模仿生物神经的PI反应。此外,AMSN还构建了一个3 × 3忆阻器阵列,以揭示大面积和多模态传感的潜力。这项工作为发展具有生物逼真性的神经形态自我保护人工神经提供了基本的突触单位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Artificial Nerve with Complementary Memristor for Neuromorphic Self-Protection

An Artificial Nerve with Complementary Memristor for Neuromorphic Self-Protection
Protective inhibition (PI) behavior is critical to human self-protection by reducing the physiological arousal of overloaded stimulation. Neuromorphic hardware mimicking PI behavior can facilitate advancements in the field of bio-realistic artificial intelligence and remains to be studied. Herein, a specially engineered complementary memristor with limited Cu embedding in porous amorphous carbon is proposed to emulate PI behavior. The depletion of Cu produces complementary switching behavior, sharing similarities with the PI response of its biological counterpart. Integrating the memristor, a resistor, and various sensors yields artificial sensory afferent nerves that intelligently demonstrate PI behavior in response to stimuli including pressure, light, and temperature. As a proof of concept, an artificial motion sensory nerve (AMSN) is constructed by sending the feedback signals of the memristor to intelligently stimulate the sciatic nerve of an anesthetized mouse to perform neuromodulation. Upon the increase of stimuli, the overstrain of the muscle is successfully inhibited, mimicking the PI response of the biological nerve. Furthermore, an AMSN is also constructed with a 3 × 3 memristor array to shed light on the potential for large area and multimodal sensing. This work provides a fundamental synaptic unit for developing bio-realistic artificial nerve for neuromorphic self-protection.
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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