Abstract
Drosophila melanogaster has been a pioneering model system for investigations into the genetic bases of behaviour. Studies of circadian activity were some of the first behaviours investigated in flies. The Drosophila Activity Monitoring (DAM) system by TriKinetics played a key role in establishing the fundamental feedback loop of the circadian clock. Although this method has many times proven to be extremely useful, it suffers from its simplification of activity to the interruption of an infrared (IR) beam. It is blind to fly movements not disrupting the beam and any modifications to this assay to achieve better resolution often requires the purchase of new and expensive modules. We required a relatively high-throughput system to explore the potential post-mating activity changes of larger Drosophila species. Rather than investing in a larger and more complex DAM system, we designed a new monitoring system that is more versatile, economic and sensitive than DAM. This new system, called DrosoVAM (Drosophila Video-assisted Activity Monitoring), is simple to implement and cost efficient, using a Raspberry Pi-controlled IR, digital video system to record multiple chambers and Python scripts that drive the deep learning software DeepLabCut, to track fly activity over multiple days.