用机器学习分析老鼠社交行为，更准且更全面。
From eye to AI: studying rodent social behavior in the era of machine Learning
- 结合计算机视觉与机器学习自动识别老鼠互动模式
- 相比人工观察，能捕捉更复杂的社交行为细节
- 适合神经科学、行为学研究者入门使用
近年来，鼠类社交行为研究正从依赖人工观察转向融合人工智能与机器学习的计算方法。传统方法易引入主观偏差，难以揭示鼠类社交互动的复杂性；而结合计算机视觉、动物行为学与神经科学的新范式，可提供更全面的行为洞察，尤其适用于社会神经科学研究。尽管如此，AI在该领域的应用仍面临诸多挑战。本文梳理了分析鼠类社交行为的主要步骤与可用工具，评估其优劣，并提出应对常见问题的实用方案，旨在帮助青年研究人员掌握这些技术，推动领域内对工具演进需求的进一步讨论。
原文摘要 · Abstract (English)
The study of rodent social behavior has shifted in the last years from relying on direct human observation to more nuanced approaches integrating computational methods in artificial intelligence (AI) and machine learning. While conventional approaches introduce bias and can fail to capture the complexity of rodent social interactions, modern approaches bridging computer vision, ethology and neuroscience provide more multifaceted insights into behavior which are particularly relevant to social neuroscience. Despite these benefits, the integration of AI into social behavior research also poses several challenges. Here we discuss the main steps involved and the tools available for analyzing rodent social behavior, examining their advantages and limitations. Additionally, we suggest practical solutions to address common hurdles, aiming to guide young researchers in adopting these methods and to stimulate further discussion among experts regarding the evolving requirements of these tools in scientific applications.
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