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神经形态纳米流体传感数字化

Neuromorphic Nanofluidic Sense Digitalization.

作者信息

Duan Zu-Ming, Xu Yi-Tong, Li Zheng, Pang Jian-Xiang, Xu Jing-Juan, Zhao Wei-Wei

机构信息

State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China.

出版信息

Angew Chem Int Ed Engl. 2025 Feb 3;64(6):e202420602. doi: 10.1002/anie.202420602. Epub 2024 Dec 5.

Abstract

Nanofluidic memristors have recently been reshaped into artificial synapses capable of mimicking many fundamental neurosynaptic patterns, while sense digitalization has been increasingly explored to link the neuromorphic devices with external equipment. By inspiration of dopaminergic nerve, here a nanofluidic nerve with sense digitalization is devised by engineering a dopamine (DA)-specific nanofluidic synapse as mediated by PC-12 cells to manage the robotic arm. Different from previous neuromorphic perception of DA via redox reaction, the aptamer-based perception here is based on biological DA recognition by its receptor as indicated by the ionic signals. Various neurosynaptic patterns are emulated with DA-dependent plasticity, based on which the digital representation of DA perception is used to control the robotic arm.

摘要

纳米流体忆阻器最近已被重塑为能够模拟许多基本神经突触模式的人工突触,同时传感数字化也越来越多地被探索用于将神经形态器件与外部设备连接起来。受多巴胺能神经的启发,本文通过设计一种由PC-12细胞介导的多巴胺(DA)特异性纳米流体突触来管理机器人手臂,从而构建了一种具有传感数字化的纳米流体神经。与以往通过氧化还原反应对多巴胺进行神经形态感知不同,这里基于适体的感知是基于其受体对生物多巴胺的识别,由离子信号指示。利用多巴胺依赖的可塑性模拟了各种神经突触模式,并在此基础上利用多巴胺感知的数字表示来控制机器人手臂。

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