Ephaptic Coupling in Ultralow‐Power Ion‐Gel Nanofiber Artificial Synapses for Enhanced Working Memory
Abstract
AbstractNeuromorphic devices are designed to replicate the energy‐efficient information processing advantages found in biological neural networks by emulating the working mechanisms of neurons and synapses. However, most existing neuromorphic devices focus primarily on functionally mimicking biological synapses, with insufficient emphasis on ion transport mechanisms. This limitation makes it challenging to achieve the complexity and connectivity inherent in biological systems, such as ephaptic coupling. Here, an ionic biomimetic synaptic device based on a flexible ion‐gel nanofiber network is proposed, which transmits information and enables ephaptic coupling through capacitance formation by ion transport with an extremely low energy consumption of just 6 femtojoules. The hysteretic ion transport behavior endows the device with synaptic‐like memory effects, significantly enhancing the performance of the reservoir computing system for classifying the MNIST handwritten digit dataset and demonstrating high efficiency in edge learning. More importantly, the devices in an array establish communication connections, exhibiting global oscillatory behaviors similar to ephaptic coupling in biological neural networks. This connectivity enables the array to perform working memory tasks, paving the way for developing brain‐like systems characterized by high complexity and vast connectivity.
Article Details
Authors (11)
Yuanxia Chen
Junfeng Xia
Department of Biomedical Engineering Guangdong Provincial Key Laboratory of Advanced Biomaterials Institute of Innovative Materials Southern University of Science and Technology Shenzhen 518055 P.R. China
Youzhi Qu
Department of Biomedical Engineering Guangdong Provincial Key Laboratory of Advanced Biomaterials Institute of Innovative Materials Southern University of Science and Technology Shenzhen 518055 P.R. China
Hongjie Zhang
State Key Laboratory of Rare Earths
Tingting Mei
Xinyi Zhu
Department of Ultrasound, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital
Guoheng Xu
Dongyang Li
Department of Materials Science and Engineering
Li Wang
The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital Zhengzhou China
Quanying Liu
Kai Xiao