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Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice
- Source :
- PLoS ONE, Vol 8, Iss 9, p e74557 (2013), PLoS ONE
- Publication Year :
- 2013
- Publisher :
- Public Library of Science (PLoS), 2013.
-
Abstract
- Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain) and BTBR T+tf/J (a mouse model for autism spectrum disorders). Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2) interacting mice, and its versatility to deal with different experimental settings and scenarios.
- Subjects :
- Behavioural analysis
Video Recording
Decision tree
lcsh:Medicine
02 engineering and technology
Social behaviour
Biology
animal behavior
video tracking
Bioinformatics
Machine learning
computer.software_genre
Mice
03 medical and health sciences
Preclinical research
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
medicine
mice social behavior
Animals
Social Behavior
lcsh:Science
030304 developmental biology
0303 health sciences
Multidisciplinary
tracking
mouse behavior
classification
business.industry
lcsh:R
medicine.disease
Video tracking
Eye tracking
Autism
lcsh:Q
020201 artificial intelligence & image processing
Artificial intelligence
business
Classifier (UML)
computer
Research Article
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....25d097940b4bbf6598ab86a9339ad823