Coulombe Vincent, Rivera Arturo Marroquin, Monfared Sadegh, Roussel David-Alexandre, Leboulleux Quentin, Peralta Modesto R, Gosselin Benoit, Labonté Benoit
CERVO Brain Research Centre, Université Laval, Québec, QC, Canada.
Smart Biomedical Microsystems Laboratory, Quebec City, QC, Canada.
Neuropsychopharmacology. 2025 May 22. doi: 10.1038/s41386-025-02126-y.
Despite recent advances, tracking individual movements safely and reliably over extended periods, particularly within complex social groups, remains a challenge. Traditional methods like color coding, tagging, and RFID tracking, while effective, have notable practical limitations. State-of-the-art neural network-based trackers often struggle to maintain individual identities in large groups for more than a few seconds. Fiducial tags such as ArUco codes present a potential solution to enable accurate tracking and identity management. However, their application to large groups of socially interacting mice in complex, enriched environments remain an open challenge. Here, we present the Tailtag system, a novel approach designed to address this challenge. The Tailtag is a non-invasive, safe, and ergonomic tail ring embedded with an ArUco marker allowing to track individual mice in colonies of up to 20 individuals in complex environments for at least seven days without performance degradation or behavioral alteration. We provide a comprehensive parameter optimization guide and practical recommendations for marker selection, for reproducibility across diverse experimental setups. Using data collected from Tailtag-equipped mice, we revealed the formation and evolution of social groups within the colony. Our analysis identified social hub regions within the vivarium where social contacts occur at different frequencies throughout one week of recordings. We quantified interactions and avoidance patterns between specific pairs of mice within the most active social hubs. Overall, our findings indicate that while the zone preferences and peer associations among the mice change over time, certain groups and pairwise interactions consistently form within the social colony.
尽管近年来取得了进展，但在较长时间内安全可靠地跟踪个体运动，尤其是在复杂的社会群体中，仍然是一项挑战。传统方法如颜色编码、标记和射频识别跟踪虽然有效，但存在明显的实际局限性。基于神经网络的先进跟踪器在大群体中往往难以在几秒钟以上保持个体身份。诸如ArUco码之类的基准标签为实现精确跟踪和身份管理提供了一种潜在的解决方案。然而，将它们应用于复杂丰富环境中大量社交互动的小鼠群体仍然是一个悬而未决的挑战。在这里，我们介绍Tailtag系统，这是一种旨在应对这一挑战的新方法。Tailtag是一种无创、安全且符合人体工程学的尾环，嵌入了一个ArUco标记，可在复杂环境中对多达20只个体的小鼠群体中的个体进行跟踪，至少持续七天，而不会出现性能下降或行为改变。我们提供了一份全面的参数优化指南以及关于标记选择的实用建议，以确保在不同实验设置下的可重复性。利用从配备Tailtag的小鼠收集的数据，我们揭示了群体内社会群体的形成和演变。我们的分析确定了饲养室内的社交枢纽区域，在为期一周的记录中，社交接触在这些区域以不同频率发生。我们对最活跃社交枢纽内特定小鼠对之间的互动和回避模式进行了量化。总体而言，我们的研究结果表明，虽然小鼠之间的区域偏好和同伴关联会随时间变化，但在社会群体中某些群体和两两之间的互动会持续形成。
