神经形态工程学
联轴节(管道)
兴奋性突触后电位
计算机科学
尖峰神经网络
Spike(软件开发)
神经科学
可扩展性
人工神经网络
生物神经网络
抑制性突触后电位
纳米技术
记忆电阻器
补品(生理学)
桥接(联网)
人工智能
电子线路
神经网络
作者
Bin Jian,F.M. Liu,Jiahui Zhou,Yang Chu,Xu Hou,Yiheng Dai,Fengwei Huo,Yaqi Hou
标识
DOI:10.1021/acs.jpclett.6c01243
摘要
Biological neural networks achieve remarkable energy efficiency through network-level interactions among coupled neurons. Emulating these coupling mechanisms physically is crucial for developing next-generation neuromorphic systems. However, current nanofluidic ionic systems remain confined to single-neuron implementations, and multineuron coupling has not yet been realized. Here, we address this gap by developing a multineuron neuromorphic circuit that couples two Hodgkin-Huxley (H-H) models via programmable nanofluidic memristors. In LTspice, the H-H models are extended into scalable neuron-axon circuits that reproduce key neurobiological behaviors, including action potential generation with an all-or-none threshold of 18 μA, spike propagation, spike trains, and refractory periods of approximately 10 ms. Nanochannel network membranes (NCNMs) engineered as artificial synapses provide tunable excitatory and inhibitory coupling. The NCNM-coupled neurons further display network-level neuromorphic functions, including excitatory or inhibitory coupling and activity-dependent transitions from phasic to tonic spiking patterns, guiding the design of bioinspired nanofluidic neural networks.
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