Artificial Spiking Neuron with Bursting Dynamics for Noise-Resistant Neuromorphic Coding Artificial Spiking Neuron with Bursting Dynamics for Noise-Resistant Neuromorphic Coding AITranslate

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DOI：https://doi.org/10.1021/acsaelm.3c00445

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Emulating complex neuronal functionalities in human brains using emerging biomimetic electronics is critical for next-generation brain-like chips and artificial general intelligence. Burst firing, featured with the repeated firing of discrete groups of spikes, is high-order neuronal dynamics for reliable signal transmission, coding, and processing. Here, we report a memristor (Pt/Co3O4–x/ITO) that can natively produce periodic voltage oscillation groups under current stimulation, capturing the burst-firing features of actual biological neurons. This behavior stems from the dynamic formation/rupture of conductive filaments regulated by the VO concentration at the grain boundaries. The burst frequency can be tuned by adjusting the driving current intensity and used to implement burst frequency coding. The bursting neuron-based artificial neural system achieves a recognition accuracy of 86% for the Fashion-MNIST tasks, under the disturbance of random noise spikes. This work provides a promising platform to realize complex neuronal dynamics and to construct robust brain-inspired neuromorphic systems.