脉冲神经网络（SNN）是更具生物可解释性的新一代人工神经网络，具有独特的信息编码处理方式、丰富的时空动力学特性、低功耗事件驱动工作模式等优势，近年来受到广泛关注并在医疗健康、工业检测、智能驾驶等方向获得探索性应用。本文介绍了SNN的基本要素和学习算法，包括经典的神经元模型、突触可塑性机制、常用的信息编码方式，分析了各类学习算法的优缺点，总结了主流的SNN软件模拟器、脉冲神经形态硬件的研究情况；细致梳理了SNN在计算机视觉、自然语言处理、推理决策等方面的研究以及行业应用场景，发现SNN在目标检测、动作识别、语义认知、语音识别等任务中具有突出的潜力，显著提升了相应的计算性能。我国在SNN领域的研究与应用发展，重在加强关键核心技术攻关、推动技术成果转化应用、持续优化产业生态格局，以尽快实现与国际先进水平的接轨；类脑复杂系统、类脑控制等理论与方法的深入研究和逐步突破，也将促进大规模SNN新模型的构建，有望拓展人工智能的更广阔应用前景。

Spiking neural network (SNN) is a new generation of artificial neural network. It is more biologically plausible and has been widely concerned by scholars owing to its unique information coding schemes, rich spatiotemporal dynamics, and event-driven operating mode with low power. In recent years, SNN has been explored and applied in many fields such as medical health, industrial detection, and intelligent driving. First, the basic elements and learning algorithms of SNN are introduced, including classical spiking neuron models, spike-timing dependent plasticity (STDP), and common information coding methods. The advantages and disadvantages of the learning algorithms are also analyzed. Then, the mainstream software simulators and neuromorphic hardware of SNN are summarized. Subsequently, the research progress and application scenarios of SNN in terms of computer vision, natural language processing, and reasoning decision are introduced. Particularly, SNN has shown strong potentials in tasks such as object detection, action recognition, semantic cognition, and speech recognition, significantly improving computational performance. Future research and application of SNN should focus on strengthening the research on key core technologies, promoting the application of technological achievements, and continuously optimizing the industrial ecology, thus to catch up with the advanced international level. Moreover, continuous research and breakthroughs of brain-inspired systems and control theories will promote the establishment of large-scale SNN models and are expected to broaden the application prospect of artificial intelligence.