A sensory–neuromorphic interface capable of environmental perception, sensory coding, and biological stimuli

神经形态工程学 感觉系统 感知 编码(社会科学) 接口(物质) 感官替代 人机交互 计算机科学 神经科学 心理学 人工智能 数学 人工神经网络 统计 气泡 最大气泡压力法 并行计算
作者
Lin Sun,Yi Du,Zichen Zhang,Siru Qin,Zixian Wang,Yue Li,Shangda Qu,Zhifang Xu,Yi Guo,Wentao Xu
出处
期刊:SmartMat [Wiley]
卷期号:5 (5) 被引量:1
标识
DOI:10.1002/smm2.1290
摘要

Abstract The sensory–neuromorphic interface is key to the application of neuromorphic electronics. Artificial spiking neurons and artificial sensory nerves have been created, and a few studies showed a complete neuromorphic system through cointegration with synaptic electronics. However, artificial synaptic devices and systems often do not work in real environments, which limits their ability to provide realistic neural simulations and interface with biological nerves. We report a sensory–neuromorphic interface that uses a fiber synapse to emulate a biological afferent nerve. For the first time, a sensing–neuromorphic interface is connected to a living organism for peripheral nerve stimulation, allowing the organism to establish a connection with its surrounding environment. The interface converts perceived environmental information into analog electrical signals and then into frequency‐dependent pulse signals, which simplify the information interface between the sensor and the pulse‐data processing center. The frequency of the interface shows a sublinear dependence on strain amplitude at different stimulus intensities, and can deliver increased frequency spikes at potentially damaging stimulus intensities, similar to the response of biological afferent nerves. To verify the application of this interface, a system that monitors strain and provides an overstrain alarm was constructed based on this afferent neural circuit. The system has a response time of <2 ms, which is compatible with the response time in biological systems. The interface can be potentially extended to process signals from almost any type of sensors for other afferent senses, and these results demonstrate the potential for neuromorphic interfaces to be applied to bionic sensory interfaces.
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