title: Automated home-cage behavioural phenotyping of mice.
abstract: Neurobehavioural analysis of mouse phenotypes requires the monitoring of mouse behaviour over long periods of time. In this study, we describe a trainable computer vision system enabling the automated analysis of complex mouse behaviours. We provide software and an extensive manually annotated video database used for training and testing the system. Our system performs on par with human scoring, as measured from ground-truth manual annotations of thousands of clips of freely behaving mice. As a validation of the system, we characterized the home-cage behaviours of two standard inbred and two non-standard mouse strains. From these data, we were able to predict in a blind test the strain identity of individual animals with high accuracy. Our video-based software will complement existing sensor-based automated approaches and enable an adaptable, comprehensive, high-throughput, fine-grained, automated analysis of mouse behaviour.
authors.affiliation: Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
authors.forename: Hueihan
authors.initials: H
authors.lastname: Jhuang
authors.forename: Estibaliz
authors.initials: E
authors.lastname: Garrote
authors.forename: Jim
authors.initials: J
authors.lastname: Mutch
authors.forename: Xinlin
authors.initials: X
authors.lastname: Yu
authors.forename: Vinita
authors.initials: V
authors.lastname: Khilnani
authors.forename: Tomaso
authors.initials: T
authors.lastname: Poggio
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Steele
authors.forename: Thomas
authors.initials: T
authors.lastname: Serre
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D005260:Female; D008297:Male; D051379:Mice