神经形态工程学
突触
锥面
频道(广播)
计算机科学
神经科学
材料科学
人工智能
电信
生物
人工神经网络
复合材料
作者
T. M. Kamsma,M. S. Klop,W. Q. Boon,Cristian Spitoni,Bodo Rueckauer,René van Roij
标识
DOI:10.1103/physrevresearch.7.013328
摘要
Fluidic iontronics offer a unique capability for emulating the chemical processes found in neurons. We extract multiple distinct chemically regulated synaptic features from an experimentally accessible conical microfluidic channel carrying functionalized surface groups, using finite-element calculations of continuum transport equations. By modeling a Langmuir-type surface reaction on the channel wall, we couple fast voltage-induced volumetric salt accumulation with a long-term channel surface charge modulation by means of fast charging and slow discharging. These nonlinear charging dynamics emerge across several orders of magnitude of reaction rates and equilibria, and are understood through an analytic approximation rooted in first principles. We show how short- and long-term potentiation and depression, frequency-dependent plasticity, and chemical-electrical signal spike-timing dependence and coincidence detection (acting like a chemical-electrical AND logic gate), akin to the NMDA mechanism for Hebbian learning in biological synapses, can all be emulated. Published by the American Physical Society 2025
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