A Brave New Homecage

Rodents used in laboratory research are housed in small groups in cages where they eat, sleep, drink, groom and interact socially. Current procedures and behavioural tests to analyse an animal's capabilities and fitness are often laborious, slow, subjective and unnatural. This project's aim is to automate such measurements within the homecage itself. If realised, the approach will offer much richer, objective data, from a non-intrusive situation that will refine the information obtained and reduce the number of animals required to achieve statistical significance. However, achieving this is technically challenging, requiring long-term recording and automated analysis of multiple animals.

The team at Actual Analytics Ltd led by Professor Douglas Armstrong proposes a ‘brave new homecage’, a system specifically designed to fit into the broadest range of existing cage and rack systems available with minimal impact. Their system looks like an enclosure for standard cages that slots into existing racks, and is compatible with both IVC and non-IVC systems, maintaining a high density of cages per rack, with minimal disruption and cabling. It contains video, illumination and tracking systems to record the movements and behaviour of multiple animals indefinitely. Data recorded from the homecage is automatically transferred to a centralised computing system, where advanced video analytics and behavioural analysis algorithms will be used to establish the behavioural profiles of animals being observed in their normal environments. This process happens continuously and indefinitely.

Full details about this CRACK IT Challenge can be found on the CRACK IT website.

Bains RS et al. (2016). Analysis of Individual Mouse Activity in Group Housed Animals of Different Inbred Strains Using a Novel Automated Home Cage Analysis System. Front. Behav. Neuroscidoi.org/10.3389/fnbeh.2016.00106.

Bains RS et al. (2017). Assessing mouse behaviour throughout the light/dark cycle using automated in-cage analysis tools. Journal of Neuroscience Methodsdoi.org/10.1016/j.jneumeth.2017.04.014.

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