Quantification of larval zebrafish motor function in multiwell plates using open-source MATLAB applications

• Published in: Nature protocols Vol. 9; no. 7; pp. 1533 - 1548
• Main Authors: Zhou, Yangzhong, Cattley, Richard T, Cario, Clinton L, Bai, Qing, Burton, Edward A
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.07.2014; Nature Publishing Group
• Subjects: 631/114/794; 631/1647/2198; 631/1647/334/1874/763; 631/378/2632; Acceleration; Algorithms; Analysis; Analytical Chemistry; Animals; Automation; Biological Techniques; Computational Biology/Bioinformatics; Danio rerio; Data analysis; Freshwater; Image Processing, Computer-Assisted - instrumentation; Image Processing, Computer-Assisted - methods; Larva; Larvae; Life Sciences; Matlab; Medical protocols; Microarrays; Motion detection; Motion perception; Motor Activity - physiology; Object recognition; Organic Chemistry; Pattern recognition; Phenotypes; Physiological aspects; Plates; Protocol; Sensorimotor integration; Software; Tracking; Video Recording - instrumentation; Video Recording - methods; Zebra fish; Zebrafish; Zebrafish - physiology; Pennsylvania; United States > US; Pittsburgh Pennsylvania
• ISSN: 1754-2189; 1750-2799; 1750-2799
• DOI: 10.1038/nprot.2014.094

In this article, the authors provide directions on using the open-source MATLAB applications LSRtrack and LSRanalyze to quantitatively follow the movements of zebrafish larvae in multi-well plates. This article describes a method to quantify the movements of larval zebrafish in multiwell plates, using the open-source MATLAB applications LSRtrack and LSRanalyze . The protocol comprises four stages: generation of high-quality, flatly illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB scripts; and implementation of validation controls. The method is reliable, automated and flexible, requires <1 h of hands-on work for completion once optimized and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine the following: positional preference; displacement, velocity and acceleration; and duration and frequency of movement events and rest periods. This approach is widely applicable to the analysis of spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multiwell plate format suitable for high-throughput applications.