March 12, 2020
Nikolas Francis and colleagues from the Kanold Laboratory at the University of Maryland – College Park have developed and shared ToneBox, a system for high-throughput operant conditioning in a mouse homecage.
Data collection for operant conditioning studies can be time-consuming and sensitive to variability in experimental conditions. An automated approach would both reduce experimental variability and allow for high-throughput training and data collection. To solve this, Francis et al. developed and shares a user-friendly automated system for training up to hundreds of mice in an auditory behavioral task. This system features a custom Matlab GUI running on a desktop which connects to a Raspberry Pi to administer auditory stimuli from a USB soundcard and collects data auditory data as well as licking data from a water spout with commercially available capacitive sensors. The parts list and build instructions are readily available from the paper and associated GitHub repository and are straight-forward enough for new users to build and operate without extensive coding or design experience. This system can collect data 24/7 for weeks on end, which allows for insight into behaviors not otherwise observable by experimenters who need to eat and sleep instead of observing mice at all hours.
The developers show how their tool can be used by training 24 C57BL/6J mice to perform auditory behavioral tasks. They report their results and find that circadian rhythms modulated overall behavioral activity as expected for nocturnal animals. Details about this study, as well as about building the device and where to find resources to create your very own ToneBox can be gleaned from reading their full paper on eNeuro.