Abstract
Behavioural experiments often happen in specialised arenas, but this may confound the analysis. To address this issue, we provide tools to study mice in the home-cage environment, equipping biologists with the possibility to capture the temporal aspect of the individual’s behaviour and model the interaction and interdependence between cage-mates with minimal human intervention. Our main contribution is the novel Global Behaviour Model (GBM) which summarises the joint behaviour of groups of mice across cages, using a permutation matrix to match the mouse identities in each cage to the model. In support of the above, we also (a) developed the Activity Labelling Module (ALM) to automatically classify mouse behaviour from video, and (b) released two datasets, ABODe for training behaviour classifiers and IMADGE for modelling behaviour.
Original language | English |
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Pages (from-to) | 1-23 |
Number of pages | 23 |
Journal | International Journal of Computer Vision |
DOIs | |
Publication status | Published - 17 Jun 2024 |
Keywords / Materials (for Non-textual outputs)
- joint behaviour model
- mouse behaviour model
- home-age analysis
- mouse behaviour data
- automated behaviour classification