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

Aharon Weissbrod, Alexander Shapiro, Genadiy Vasserman, Liat Edry, Molly Dayan, Assif Yitzhaky, Libi Hertzberg, Ofer Feinerman and Tali Kimchi ()
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Aharon Weissbrod: Weizmann Institute of Science
Alexander Shapiro: Weizmann Institute of Science
Genadiy Vasserman: Weizmann Institute of Science
Liat Edry: Weizmann Institute of Science
Molly Dayan: Weizmann Institute of Science
Assif Yitzhaky: Weizmann Institute of Science
Libi Hertzberg: Weizmann Institute of Science
Ofer Feinerman: Weizmann Institute of Science
Tali Kimchi: Weizmann Institute of Science

Nature Communications, 2013, vol. 4, issue 1, 1-10

Abstract: Abstract 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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3018

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DOI: 10.1038/ncomms3018

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