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

Abstract

AbstractBackgroundThe 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.MethodsWe 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.ResultsPcp2-Ppp3r1mutant animals showed a significant increase in the number of missteps and increased time to traverse the beam.ConclusionWe 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 statementThe 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.