Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning - Institut Pasteur Access content directly
Journal Articles Nature Biomedical Engineering Year : 2019

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

Nicolas Torquet
Thierry Legou
  • Function : Author
  • PersonId : 850065
  • IdRef : 257835849
Philippe Faure

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.

Dates and versions

pasteur-02344329 , version 1 (04-11-2019)

Identifiers

Cite

Fabrice de Chaumont, Elodie Ey, Nicolas Torquet, Thibault Lagache, Stéphane Dallongeville, et al.. Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning. Nature Biomedical Engineering, 2019, 3, pp.930-942. ⟨10.1038/s41551-019-0396-1⟩. ⟨pasteur-02344329⟩
92 View
1 Download

Altmetric

Share

Gmail Facebook X LinkedIn More