Megabouts:斑马鱼运动分析的灵活管道

Adrien Jouary, Alexandre Laborde, Pedro T. Silva, J. Miguel Mata, Joao C. Marques, Elena Collins, Randall T. Peterson, Christian K. Machens, Michael B. Orger
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引用次数: 0

摘要

准确量化动物行为对于推动神经科学发展和定义可靠的生理标记至关重要。我们介绍的 Megabouts(megabouts.ai)是一个软件包,可在不同实验设置下对斑马鱼幼虫的运动分析进行标准化。该软件的灵活性是通过变形神经网络实现的,它允许对动作进行分类,而不受跟踪方法或帧速率的限制。我们展示了 Megabouts 通过高通量、高分辨率行为分析量化感觉运动转换和提高对药物诱导表型敏感性的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Megabouts: a flexible pipeline for zebrafish locomotion analysis
Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts' ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.
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