Detecting ataxia using an automated analysis of motor coordination and balance of mice on the balance beam

Abstract Background The balance beam assay is a well-known paradigm to assess motor coordination in mouse models of neurodegenerative diseases. Classically, these experiments have been quantified using manual annotation, which is time-consuming and prone to inter-experimenter variability. Methods We present an open-source analysis pipeline that allows for the automated quantification of motor function. Using an established ataxia model, we validated the pipeline by comparing its output to three independent observers. Results Pcp2-Ppp3r1 mutant animals showed a significant increase in the number of missteps and increased time to traverse the beam. Conclusion We show that our pipeline can reliably report crossing time, missteps, stops, and falls, thereby offering a high-throughput option with increased inter-experimenter reliability for the analysis of balance beam data. Significance statement The analysis of mouse behaviour and motor coordination experiments often lacks automation and standardisation and is thus time-consuming and prone to inter-experimenter variability and poor reproducibility. The balance beam assay is a well-established motor coordination paradigm and currently lacks such an automated, standardised analysis platform. We have developed an open-source pipeline that allows for the automated analysis of crossing time, missteps, stops, and falls. Together with a standardised, easy to assemble balance beam setup, our pipeline offers a cost-effective, and high-throughput option to generate and analyse balance beam data with increased inter-experimenter and intra-experimenter reliability.