霍奇金-赫胥黎模型
稳态可塑性
记忆电阻器
神经科学
计算机科学
突触可塑性
变质塑性
物理
生物
量子力学
生物化学
受体
作者
Yue Yang,Xumeng Zhang,Pei Chen,Lingli Cheng,Yanting Ding,Chao Li,Jie Yu,Qi Liu
标识
DOI:10.1109/led.2024.3456816
摘要
Artificial neurons based on the Hodgkin-Huxley (H-H) models could mimic the richest firing patterns, showing great potential in building high-intelligent systems. Emerging devices, such as NbO2-based threshold-switching devices, exhibit more advantages in constructing H-H neuron circuits compared to conventional transistors. However, the on-chip integration of the memristive H-H neuron circuit remains unexplored, limiting its practical applications in hardware. Here, we design and fabricate a fully integrated memristive H-H neuron circuit and achieve all-or-nothing, refractory period, integrator, class 1 excitation, tonic spiking, subthreshold oscillation, tonic bursting, and mixed-mode firing behaviors. We also demonstrate the homeostatic plasticity based on integrated H-H neuron, specifically, the neuron increases threshold spontaneously when receiving an excessively strong input to avoid the superexcitation in the neuron. This work verifies the feasibility of building an integrated memristive H-H neuron and lays the foundation for building high-bionic neuromorphic systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI