This study emphasizes the benefits of open-source software such as DeepLabCut (DLC) and R to automate, customize and enhance data analysis of motor behavior. We recorded 2 different spinocerebellar ataxia type 6 mouse models while performing the classic beamwalk test, tracked multiple body parts using the markerless pose-estimation software DLC and analyzed the tracked data using self-written scripts in the programming language R. The beamwalk analysis script (BAS) counts and classifies minor and major hindpaw slips with an 83% accuracy compared to manual scoring. Nose, belly and tail positions relative to the beam, as well as the angle at the tail base relative to the nose and tail tip were determined to characterize motor deficits in greater detail. Our results found distinct ataxic abnormalities such as an increase in major left hindpaw slips and a lower belly and tail position in both SCA6 ataxic mouse models compared to control mice at 18 months of age. Furthermore, a more detailed analysis of various body parts relative to the beam revealed an overall lower body position in the SCA684Q compared to the CT-longQ27PC mouse line at 18 months of age, indicating a more severe ataxic deficit in the SCA684Q group.
Keywords: DeepLabCut; Gait analysis; Markerless pose estimation; Open-source; Spinocerebellar ataxia type 6.
© 2024. The Author(s).