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

Author

Listed:
  • 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
    The Emotion-Cognition Research Center, Shalvata Mental Health Center, Sackler Faculty of Medicine, Tel Aviv University)

  • Ofer Feinerman

    (Weizmann Institute of Science)

  • Tali Kimchi

    (Weizmann Institute of Science)

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.

Suggested Citation

  • Aharon Weissbrod & Alexander Shapiro & Genadiy Vasserman & Liat Edry & Molly Dayan & Assif Yitzhaky & Libi Hertzberg & Ofer Feinerman & Tali Kimchi, 2013. "Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment," Nature Communications, Nature, vol. 4(1), pages 1-10, October.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3018
    DOI: 10.1038/ncomms3018
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    Cited by:

    1. Christian L. Ebbesen & Robert C. Froemke, 2022. "Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    2. Zhi-Ming Qian & Xi En Cheng & Yan Qiu Chen, 2014. "Automatically Detect and Track Multiple Fish Swimming in Shallow Water with Frequent Occlusion," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-12, September.

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