Ohayon, S. and Avni, O. and Taylor, A. L. and Egnor, R. and Perona, P. (2013) Automated long-term tracking and analysis of social behavior in groups of mice. Journal of Molecular Neuroscience, 51 (S1). S86-S87. ISSN 0895-8696. https://resolver.caltech.edu/CaltechAUTHORS:20140423-125331299
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Abstract
Social interaction in a group of animals has been a difficult area of study since behavior develops over long periods of time, requires laborious time consuming manual annotation, and suffers from subjective scoring. We present a computer vision based method for tracking multiple mice over long periods of time (days) without mixing individual identities within the group. Our system computes the trajectory of each individual and reconstructs high order statistical ethograms (e.g. relative posture, preferred locations, following, approaching, etc.). These correlates of social interaction can be used to study courtship, dominance and aggression, which may develop over the course of days and may not be observable in acute experiments. We show the applicability of our method in studying how social hierarchy develops between a group of two males and two females over the course of 5 days.
Item Type: | Article | ||||||
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Additional Information: | © 2013 Springer Science+Business Media New York. | ||||||
Issue or Number: | S1 | ||||||
Record Number: | CaltechAUTHORS:20140423-125331299 | ||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20140423-125331299 | ||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
ID Code: | 45147 | ||||||
Collection: | CaltechAUTHORS | ||||||
Deposited By: | Tony Diaz | ||||||
Deposited On: | 23 Apr 2014 19:59 | ||||||
Last Modified: | 03 Oct 2019 06:27 |
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