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

Emulating complex neuronal functionalities in human brainsusingemerging biomimetic electronics is critical for next-generation brain-likechips and artificial general intelligence. Burst firing, featuredwith the repeated firing of discrete groups of spikes, is high-orderneuronal dynamics for reliable signal transmission, coding, and processing.Here, we report a memristor (Pt/Co3O4-x /ITO) that can natively produce periodic voltageoscillation groups under current stimulation, capturing the burst-firingfeatures of actual biological neurons. This behavior stems from thedynamic formation/rupture of conductive filaments regulated by the V (O) concentration at the grain boundaries. Theburst frequency can be tuned by adjusting the driving current intensityand used to implement burst frequency coding. The bursting neuron-basedartificial neural system achieves a recognition accuracy of 86% forthe Fashion-MNIST tasks, under the disturbance of random noise spikes.This work provides a promising platform to realize complex neuronaldynamics and to construct robust brain-inspired neuromorphic systems.