TY - JOUR
T1 - Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment
AU - Weissbrod, Aharon
AU - Shapiro, Alexander
AU - Vasserman, Genadiy
AU - Edry, Liat
AU - Dayan, Molly
AU - Yitzhaky, Assif
AU - Hertzberg, Libi
AU - Feinerman, Ofer
AU - Kimchi, Tali
N1 - DoD US Army Autism Research Program - Resource Development Award [AR100419]; Yeda-Sela grant; Jonathan Birbach Foundation; Israel Science Foundation-Grant [1694/10]We thank A. Jahanfard and B. Pasmantirer for mechanical designs; A. Harmelin and his staff for their veterinary support; Y. Toledo and G. Gitliz for software designs and technical supports; and G. Brodsky for art designs. N. Barak for data analysis assistant; N. Sobel for the advice and professional support; B. Nadler and Y. Dudai for the helpful advice on the manuscript; E. Domany and T. Flash for their assistance with the initial data analysis. This work was supported by the DoD US Army Autism Research Program - Resource Development Award no. AR100419 (T.K), Yeda-Sela grant (T.K), Jonathan Birbach Foundation (T.K.) and the Israel Science Foundation-Grant no. 1694/10 (O.F.).
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84879612197&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/ncomms3018
DO - https://doi.org/10.1038/ncomms3018
M3 - مقالة
C2 - 23771126
SN - 2041-1723
VL - 4
JO - Nature Communications
JF - Nature Communications
M1 - 2018
ER -