Virtual reality for animal navigation with camera-based optical flow tracking

Background Virtual reality combined with spherical treadmills is used across species for studying neural circuits underlying navigation. New Method We developed an optical flow-based method for tracking treadmil ball motion in real-time using a single high-resolution camera. Results Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms. Comparison with Existing Method(s) Optical flow based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration. Conclusions A fast system for rotational ball motion tracking suitable for virtual reality animal behavior across different scales was developed and characterized.