Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment

• Published in: Nature communications 2013, Vol.4 (1), p.2018-2018, Article 2018
• Main Authors: Weissbrod, Aharon, Shapiro, Alexander, Vasserman, Genadiy, Edry, Liat, Dayan, Molly, Yitzhaky, Assif, Hertzberg, Libi, Feinerman, Ofer, Kimchi, Tali
• Format: Article
• Language: English
• Subjects: 631/1647/2198; 631/378/2645; Animals; Automation; Behavior, Animal - physiology; Crosses, Genetic; Data Collection; Environment; Female; Hierarchy, Social; Humanities and Social Sciences; Locomotion; Male; Mice; Mice, Inbred C57BL; multidisciplinary; Phenotype; Radio Frequency Identification Device - methods; Science; Science (multidisciplinary); Social Behavior; Time Factors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms3018

Social behaviour has a key role in animal survival across species, ranging from insects to primates and humans. However, the biological mechanisms driving natural interactions between multiple animals, over long-term periods, are poorly studied and remain elusive. Rigorous and objective quantification of behavioural parameters within a group poses a major challenge as it requires simultaneous monitoring of the positions of several individuals and comprehensive consideration of many complex factors. Automatic tracking and phenotyping of interacting animals could thus overcome the limitations of manual tracking methods. Here we report a broadly applicable system that automatically tracks the locations of multiple, uniquely identified animals, such as mice, within a semi-natural setting. The system combines video and radio frequency identified tracking data to obtain detailed behavioural profiles of both individuals and groups. We demonstrate the usefulness of these data in characterizing individual phenotypes, interactions between pairs and the collective social organization of groups. Quantification of the behavioural phenotype of animals within a group requires simultaneous position and identity tracking of multiple individuals. Here the authors report an automated tracking system that combines video- and RFID-tracking data and allows behavioural phenotyping of uniquely identified group-living animals.