We published an invited review entitled “自旋类脑神经形态计算” (Spin-based Brain-like Neuromorphic Computing) in [Journal of Sichuan Normal University (Natural Science) 48(2), 176-191 (2025)]. Brain-inspired neuromorphic computing aims to simulate and implement the information processing and learning capabilities of the biological brain, with one of its key ideas being to mimic the behavior of biological neurons and synapses to achieve information transmission, processing, and storage. Owing to their non-volatility, high speed, low power consumption, nearly infinite endurance, and inherent nonlinearity, spintronic devices have been widely explored and have shown remarkable performance in neuromorphic computing. In this invited review, we systematically introduce and summarize various spintronic effects, including magnetoresistance effects, spin-transfer torque and spin-orbit torque effects, voltage-controlled magnetic anisotropy, and nonlinear magnetization dynamics. Taking the applications of various spintronic devices in reservoir computing, Ising machines, spiking neural networks, and true random number generators as examples, we present an outlook on the prospects and trends of spin-based neuromorphic computing hardware for future artificial-intelligence chips. Congratulations to Shuai Zhang and Co-workers!