Brain-inspired computing, drawing inspiration from the fundamental structure and information-processing mechanisms of the human brain, has gained significant momentum in recent years. It has emerged as a research paradigm centered around brain-computer dual-driven and multi-network integration. One noteworthy instance of this paradigm is the Hybrid Neural Network (HNN), which integrates computer-science-oriented artificial neural networks with neuroscience-oriented spiking neural networks. HNNs exhibit distinct advantages in various intelligent tasks, including perception, cognition, and learning. This paper presents a comprehensive review of HNNs with an emphasis on their origin, concepts, biological perspective, construction framework, and supporting systems. Furthermore, insights and suggestions for potential research directions are provided aiming to propel the advancement of the HNN paradigm.

中文翻译：

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通过混合神经网络推进类脑计算

类脑计算从人脑的基本结构和信息处理机制中汲取灵感，近年来获得了巨大的发展势头。它已成为以脑机双驱动、多网络融合为中心的研究范式。这一范式的一个值得注意的例子是混合神经网络（HNN），它将面向计算机科学的人工神经网络与面向神经科学的尖峰神经网络集成在一起。HNN 在各种智能任务中表现出明显的优势，包括感知、认知和学习。本文对 HNN 进行了全面的回顾，重点介绍了 HNN 的起源、概念、生物学视角、构建框架和支持系统。此外，还提供了对潜在研究方向的见解和建议，旨在推动 HNN 范式的进步。