Long-duration animal tracking in difficult lighting conditions

• DOI: 10.1038/srep10432
• Publication Date: 2015-07-01T09:17:16Z
• Authors: Ulrich Stern; Edward Y. Zhu; Ruo He; Chung-Hui Yang
• Keywords: FOS: Computer and information sciences; 0301 basic medicine; Behavior; Time Factors; Behavior, Animal; Animal; Ultraviolet Rays; Computer Vision and Pattern Recognition (cs.CV); 590; Computer Science - Computer Vision and Pattern Recognition; Quantitative Biology - Quantitative Methods; Article; 03 medical and health sciences; Drosophila melanogaster; FOS: Biological sciences; Animals; Lighting; Quantitative Methods (q-bio.QM); Ovum

AbstractHigh-throughput analysis of animal behavior requires software to analyze videos. Such software typically depends on the experiments’ being performed in good lighting conditions, but this ideal is difficult or impossible to achieve for certain classes of experiments. Here, we describe techniques that allow long-duration positional tracking in difficult lighting conditions with strong shadows or recurring “on”/“off” changes in lighting. The latter condition will likely become increasingly common, e.g., for Drosophila due to the advent of red-shifted channelrhodopsins. The techniques enabled tracking with good accuracy in three types of experiments with difficult lighting conditions in our lab. Our technique handling shadows relies on single-animal tracking and on shadows’ and flies’ being accurately distinguishable by distance to the center of the arena (or a similar geometric rule); the other techniques should be broadly applicable. We implemented the techniques as extensions of the widely-used tracking software Ctrax; however, they are relatively simple, not specific to Drosophila and could be added to other trackers as well.