Abstract
Monitoring the activity of mice within their home cage is proving to be a powerful tool for revealing subtle and early-onset phenotypes in mouse models. Video tracking, in particular, lends itself to automated machine-learning technologies that have the potential to improve the manual annotations carried out by humans. This type of recording and analysis is particularly powerful in objective phenotyping, monitoring behaviors with no experimenter intervention. In this study, we focus on non-evoked voluntary behaviors, which do not require any contact with the animal or exposure to specialist equipment. We show that the monitoring of climbing on the wire cage lid of a standard individually ventilated cage (IVC) yields reproducible data reflecting complex phenotypes of individual mouse inbred strains and of a widely used mouse model of neurodegeneration. In addition, performing such measurements in the home-cage environment, over several 24-hour periods, allows for the collection of comprehensive behavioral and activity data, which reveals prolific sexual dimorphism and biphasic changes in locomotor activity. Here we present data from home-cage analysis, which reveals the complexity of unprovoked behavior in both wild-type and mutant mice. This has the potential to greatly enhance the characterization of mouse strains, detect early and subtle signs of disease and increase reproducibility in preclinical studies.
Competing Interest Statement
The authors RS and JA were/are employed by or were shareholders in Actual Analytics Ltd at the time the research was performed and therefore declare a competing financial interest. Actual HCA is commercially available from Actual Analytics Ltd.