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Nat Biomed Eng. 2019 May 20. doi: 10.1038/s41551-019-0396-1. [Epub ahead of print]

Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Author information

1
Institut Pasteur, BioImage Analysis Unit, CNRS UMR 3691, Paris, France. fabrice.de-chaumont@pasteur.fr.
2
Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, University Paris-Diderot, Paris, France. elodie.ey@pasteur.fr.
3
Sorbonne Université, CNRS UMR 8246, INSERM, Neurosciences Paris Seine - Institut de Biologie Paris-Seine, Paris, France.
4
Institut Pasteur, BioImage Analysis Unit, CNRS UMR 3691, Paris, France.
5
Institut Pasteur, FabLab, Center for Innovation and Technological research, Paris, France.
6
Aix-Marseille Université, CNRS, LPL, UMR 7309, Aix-en-Provence, France.
7
Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, University Paris-Diderot, Paris, France.
8
Institut Pasteur, BioImage Analysis Unit, CNRS UMR 3691, Paris, France. jean-christophe.olivo-marin@pasteur.fr.

Abstract

Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time analysis of the behaviour of mice housed in groups of up to four over several days and in enriched environments. The method combines computer vision through a depth-sensing infrared camera, machine learning for animal and posture identification, and radio-frequency identification to monitor the quality of mouse tracking. It tracks multiple mice accurately, extracts a list of behavioural traits of both individuals and the groups of mice, and provides a phenotypic profile for each animal. We used the method to study the impact of Shank2 and Shank3 gene mutations-mutations that are associated with autism-on mouse behaviour. Characterization and integration of data from the behavioural profiles of Shank2 and Shank3 mutant female mice revealed their distinctive activity levels and involvement in complex social interactions.

PMID:
31110290
DOI:
10.1038/s41551-019-0396-1

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