Of Mice and Mates: Automated Classification and Modelling of Mouse Behaviour in Groups using a Single Model across Cages

Michael P. J. Camilleri, Rasneer S. Bains, Christopher K. I. Williams
6/5/2023
cs.CVcs.LGstat.ML

No official code found. Best implementation: michael-camilleri/Mice-N-Mates (0 stars, GPL-3.0, last commit 2024-05-27).

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 Group 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.

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Code Implementations(1)

michael-camilleri/Mice-N-MatesCommunity100%
GPL-3.0
00Python, Jupyter NotebookJan 22, 20242 years agoGPL-3.0

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Cite this paper

@article{camilleri2023mice,
  title  = {Of Mice and Mates: Automated Classification and Modelling of Mouse Behaviour in Groups using a Single Model across Cages},
  author = {Michael P. J. Camilleri and Rasneer S. Bains and Christopher K. I. Williams},
  year   = {2023},
  eprint = {2306.03066},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.03066v2}
}

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