The Tailtag: A multi-mouse tracking system to measure social dynamics in complex environments
摘要
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.