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Socially dominant male mice in social hierarchies identified via automated RFID tracking exhibit elevated activity levels and circulating markers of higher metabolic demand

Seese, S. O.; Milewski, T. M.; Fusillo, M.; Curley, J.

2026-08-27 animal behavior and cognition
10.64898/2026.08.26.747333 bioRxiv
Show abstract

Dominance hierarchies are a fundamental aspect of social organization, enabling animals to minimize aggression and optimize access to resources. Previous studies have highlighted the energetic and physiological demands of dominant status, as well as the behavioral flexibility required of subordinates to navigate these hierarchies. Despite advancements in automated behavior tracking, limitations persist in tracking fine-scale, real-time interactions within complex social environments. Here, we developed and validated a novel RFID-based system to continuously monitor dominance hierarchies in group-housed male mice over 10 days. This system enabled unbiased behavioral inference across light phases and revealed spatial and temporal patterns of dominance behavior undetectable through traditional live-scored methods. Automated tracking accurately identified alpha individuals and consistently inferred linear hierarchies across cohorts, with greater precision for higher-ranked individuals. Behavioral metrics, such as transition frequencies and proximity to food zones, were consistent with dominance driven activity. Hormonal analyses revealed that higher-ranked mice exhibited increased leptin and peptide YY, consistent with heightened activity and satiety signaling, while lower C-peptide levels reflected greater metabolic demands of dominance. Furthermore, dominance rank was associated with differences in light-dark activity, which were in turn related to circulating hormone profiles. This study demonstrates the utility of automated RFID tracking in capturing dominance hierarchies with temporal and spatial granularity, while revealing links between social rank, metabolic regulation, and activity patterns advancing our understanding of social behavior dynamics.

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