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 homecage 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. We develop
the Activity Labelling Module (ALM) to automatically classify mouse behaviour
from video, and a novel Group Behaviour Model (GBM) for summarising their joint
behaviour across cages, using a permutation matrix to match the mouse
identities in each cage to the model. We also release two datasets, ABODe for
training behaviour classifiers and IMADGE for modelling behaviour.

研究者提供了工具来研究老鼠在家庭笼环境中的行为，包括使用自动分类老鼠行为的 ALM 以及使用置换矩阵来匹配每个笼子中老鼠身份的 Group Behaviour Model，为生物学家提供了捕捉个体行为和模拟笼友间互动关系和相互依赖性的可能性。