REVS: A new open-source platform for high-resolution analysis of rodent wheel running behavior

IF 2.3 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods Pub Date : 2025-09-12 DOI:10.1016/j.jneumeth.2025.110581

James L. Bonanno , Ciara F. O’Brien , William B.J. Cafferty

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引用次数: 0

Abstract

Background

Rodent 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 method

We 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.

Results

We 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 methods

Unlike 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.

Conclusions

REVS 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.

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REVS：一个新的开源平台，用于高分辨率分析啮齿类动物的轮滑行为。

背景：啮齿动物轮跑在神经科学和临床前研究中被广泛用于评估运动功能、创伤或疾病后恢复、昼夜节律和运动生理学。然而，大多数现有的轮式跑步系统提供的指标有限，硬件缺乏灵活性，或者需要昂贵的专有软件，这降低了它们对详细行为表型的有用性，特别是在损伤或康复模型中。新方法：我们开发了REVS (Revolution Evaluation and Visualization Software)，这是一个低成本、开源的硬件和软件平台，用于分析和可视化啮齿动物的轮滑行为。REVS使用霍尔效应传感器捕获车轮转速，并计算13个日级行为指标以及详细的约级数据。用户可以交互式地探索高分辨率的时间特征，并以兼容开放数据共享（ODC）的格式导出数据。REVS支持可定制的车轮类型，便于使用的动物与运动和/或感觉障碍。结果：我们使用部分脊髓损伤的小鼠模型验证了REVS，其中精细运动控制受损。REVS检测到损伤后13项行为指标中的10项存在损伤，不同措施的恢复轨迹各不相同。主成分分析显示，恢复与比赛质量和强度密切相关，而不是时间。与现有方法的比较：与商业和开源系统不同，REVS提供了更详细的指标、可定制的车轮兼容性、与常见vivarium硬件的无缝融合、集成的数据可视化和odc兼容的数据导出。它还支持跨个人和组的灵活分析。结论：REVS为啮齿动物研究中的颗粒行为表型提供了一个强大的、可扩展的工具，提高了可重复性，并揭示了与损伤、恢复和干预相关的细微运动变化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Neuroscience Methods 医学-神经科学

CiteScore

7.10

自引率

3.30%

发文量

226

审稿时长

52 days

期刊介绍： The Journal of Neuroscience Methods publishes papers that describe new methods that are specifically for neuroscience research conducted in invertebrates, vertebrates or in man. Major methodological improvements or important refinements of established neuroscience methods are also considered for publication. The Journal''s Scope includes all aspects of contemporary neuroscience research, including anatomical, behavioural, biochemical, cellular, computational, molecular, invasive and non-invasive imaging, optogenetic, and physiological research investigations.