神经形态工程学
感知
计算机科学
神经科学
人工智能
心理学
人工神经网络
作者
Yao Yao,Robert M. Pankow,Wei Huang,Cui Wu,Lin Gao,Yongjoon Cho,Jianhua Chen,Dayong Zhang,Sakshi Sharma,Xiaoxue Liu,Yuyang Wang,Bo Peng,Sein Chung,Kilwon Cho,Simone Fabiano,Zunzhong Ye,Jianfeng Ping,Tobin J. Marks,Antonio Facchetti
标识
DOI:10.1073/pnas.2414879122
摘要
Human perception systems are highly refined, relying on an adaptive, plastic, and event-driven network of sensory neurons. Drawing inspiration from Nature, neuromorphic perception systems hold tremendous potential for efficient multisensory signal processing in the physical world; however, the development of an efficient artificial neuron with a widely calibratable spiking range and reduced footprint remains challenging. Here, we report an efficient organic electrochemical neuron (OECN) with reduced footprint (<37 mm 2 ) based on high-performance vertical OECT (vOECT) complementary circuitry enabled by an advanced n-type polymer for balanced p-/n-type vOECT performance. The OECN exhibits outstanding neuronal characteristics, capable of producing spikes with a widely calibratable state-of-the art firing frequency range of 0.130 to 147.1 Hz. Leveraging this capability, we develop a neuromorphic perception system that integrates mechanical sensors with the OECN and integrates them with an artificial synapse for tactile perception. The system successfully encodes tactile stimulations into frequency-dependent spikes, which are further converted into postsynaptic responses. This bioinspired design demonstrates significant potential to advance cyborg and neuromorphic systems, providing them with perceptual capabilities.
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