REVS: A New Open-Source Platform for High-Resolution Analysis of Rodent Wheel Running Behavior

Abstract

BackgroundRodent wheel running is widely used in neuroscience and preclinical research to assess locomotor function, recovery post-trauma or disease, circadian rhythms, and exercise physiology. However, most existing wheel-running systems offer limited metrics, lack flexibility in hardware, or require costly proprietary software, reducing their usefulness for detailed behavioral phenotyping--especially in models of injury or rehabilitation. New methodWe developed REVS (Revolution Evaluation and Visualization Software), a low-cost, open-source hardware and software platform for analyzing and visualizing rodent wheel running behavior. REVS captures wheel revolutions using Hall effect sensors and computes 13 day-level behavioral metrics along with detailed bout-level data. Users can interactively explore high-resolution temporal features and export data in Open Data Commons (ODC)-compatible formats. REVS supports customizable wheel types, facilitating use in animals with motor and/or sensory impairments. ResultsWe validated REVS using a mouse model of partial spinal cord injury, where fine motor control is compromised. REVS detected impairments in 10 of 13 behavioral metrics post-injury, with varied recovery trajectories across measures. Principal component analysis revealed that recovery was closely linked to bout quality and intensity, rather than timing. Comparison with existing methodsUnlike commercial and open-source systems, REVS offers more detailed metrics, customizable wheel compatibility, seamless blending with common vivarium hardware, integrated data visualizations, and ODC-compatible data export. It also supports flexible analysis across individuals and groups. ConclusionsREVS provides a powerful, scalable tool for granular behavioral phenotyping in rodent studies, enhancing reproducibility and revealing insights into subtle locomotor changes associated with injury, recovery, and intervention. HighlightsO_LIREVS enables detailed analysis of voluntary wheel running in rodents C_LIO_LIThe platform combines low-cost hardware with open-source analysis software C_LIO_LIREVS computes 13 behavioral metrics across daily and bout-level timescales C_LIO_LIWe identified a unique lesion and recovery profile after partial spinal cord injury C_LIO_LIREVS supports ODC-compatible data export for transparency and reuse C_LI