Deciphering the rich repertoire of mouse behavior is crucial for understanding the functions of both the healthy and diseased brain. However, the current landscape lacks effective, affordable, and accessible methods for acquiring such data, especially when employing multiple cameras simultaneously. We have developed REVEALS (Rodent Behavior Multi-Camera Laboratory Acquisition), a graphical user interface for acquiring rodent behavioral data via commonly used USB3 cameras. REVEALS allows for user-friendly control of recording from one or multiple cameras simultaneously while streamlining the data acquisition process, enabling researchers to collect and analyze large datasets efficiently. We release this software package as a stand-alone, open-source framework for researchers to use and modify according to their needs. We describe the details of the graphical user interface implementation, including the camera control software and the video recording functionality. We validate results demonstrating the graphical user interface's stability, reliability, and accuracy for capturing rodent behavior using DeepLabCut in various behavioral tasks. REVEALS can be incorporated into existing DeepLabCut, MoSeq, or other custom pipelines to analyze complex behavior. In summary, REVEALS offers an interface for collecting behavioral data from single or multiple perspectives, which, when combined with deep learning algorithms, enables the scientific community to identify and characterize complex behavioral phenotypes.
Keywords: behavioral tracking; mouse models; multi-camera software; neuroscience; unbiased behavioral analysis.
© The Author(s) 2024. Published by Oxford University Press.