动物实验长期以来一直是神经学研究的基石，但它面临着日益增长的科学、伦理和经济挑战。人工智能 (AI) 的进步为用更贴近人类且更高效的方法取代动物测试提供了新的机会。本文探讨了脑类器官、计算模型和机器学习等人工智能技术在彻底改变神经学研究并减少对动物模型的依赖方面的潜力。这些方法可以更好地概括人脑生理学、预测药物反应并揭示神经系统疾病的新见解。它们还提供了比动物实验更快、更便宜、更合乎道德的替代方案。案例研究证明人工智能能够加速阿尔茨海默氏症的药物发现、预测神经毒性、个性化帕金森氏症的治疗以及恢复瘫痪的运动。虽然验证和整合这些技术仍然面临挑战，但科学、经济、实用和道德优势正在推动神经病学领域向基于人工智能、无动物研究的范式转变。通过跨部门的持续投资和合作，人工智能有望加速开发更安全、更有效的神经系统疾病疗法，同时显着减少动物使用。前进的道路需要这些技术的不断开发和验证，但未来它们在很大程度上取代神经病学中的动物实验的可能性似乎越来越大。这一转变预示着一个更加人性化、与人类相关和创新的大脑研究的新时代。

Animal experimentation has long been a cornerstone of neurology research, but it faces growing scientific, ethical, and economic challenges. Advances in artificial intelligence (AI) are providing new opportunities to replace animal testing with more human-relevant and efficient methods. This article explores the potential of AI technologies such as brain organoids, computational models, and machine learning to revolutionize neurology research and reduce reliance on animal models. These approaches can better recapitulate human brain physiology, predict drug responses, and uncover novel insights into neurological disorders. They also offer faster, cheaper, and more ethical alternatives to animal experiments. Case studies demonstrate AI's ability to accelerate drug discovery for Alzheimer's, predict neurotoxicity, personalize treatments for Parkinson's, and restore movement in paralysis. While challenges remain in validating and integrating these technologies, the scientific, economic, practical, and moral advantages are driving a paradigm shift towards AI-based, animal-free research in neurology. With continued investment and collaboration across sectors, AI promises to accelerate the development of safer and more effective therapies for neurological conditions while significantly reducing animal use. The path forward requires the ongoing development and validation of these technologies, but a future in which they largely replace animal experiments in neurology appears increasingly likely. This transition heralds a new era of more humane, human-relevant, and innovative brain research.