The Neurotox Lab, School of Science, RMIT University, Melbourne, Victoria, Australia.
Environ Toxicol Chem. 2022 Oct;41(10):2342-2352. doi: 10.1002/etc.5434. Epub 2022 Sep 6.
Behavioral phenotypic analysis is an emerging and increasingly important toolbox in aquatic ecotoxicology. In this regard digital video recording has recently become a standard in obtaining behavioral data. Subsequent analysis requires applications of specialized software for detecting and reconstructing animal locomotory trajectories as well as extracting quantitative biometric endpoints associated with specific behavioral traits. Despite some profound advantages for behavioral ecotoxicology, there is a notable lack of standardization of procedures and guidelines that would aid in consistently acquiring high-quality digital videos. The latter are fundamental for using animal tracking software successfully and to avoid issues such as identification switching, incorrect interpolation, and low tracking visibility. Achieving an optimized tracking not only saves user time and effort to analyze the results but also provides high-fidelity data with minimal artifacts. In the present study we, for the first time, provide an easily accessible guide on how to set up and optimize digital video acquisition while minimizing pitfalls in obtaining the highest-quality data for subsequent animal tracking. We also discuss straightforward digital video postprocessing techniques that can be employed to further enhance tracking consistency or improve the videos that were acquired in otherwise suboptimal settings. The present study provides an essential guidebook for any aquatic ecotoxicology studies that utilize digital video acquisition systems for evaluation of behavioral endpoints. Environ Toxicol Chem 2022;41:2342-2352. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
行为表型分析是水生毒理学中一个新兴且日益重要的工具包。在这方面,数字视频记录最近已成为获取行为数据的标准。随后的分析需要应用专门的软件来检测和重建动物的运动轨迹,并提取与特定行为特征相关的定量生物计量终点。尽管数字视频在行为毒理学方面具有一些显著的优势,但在获取高质量数字视频方面,程序和指南的标准化程度明显不足。后者是成功使用动物跟踪软件并避免识别切换、不正确插值和跟踪可见度低等问题的基础。实现优化的跟踪不仅可以节省用户分析结果的时间和精力,还可以提供具有最小伪影的高保真数据。在本研究中,我们首次提供了一个易于访问的指南,介绍如何在最小化获得最高质量数据的陷阱的同时设置和优化数字视频采集,以便随后进行动物跟踪。我们还讨论了简单的数字视频后处理技术,这些技术可用于进一步提高跟踪的一致性,或改进在其他不理想设置下获取的视频。本研究为任何利用数字视频采集系统评估行为终点的水生毒理学研究提供了一本必不可少的指南。