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一种基于功能独立性测量(FIM)的果蝇幼虫长期瓶内监测系统。

An FIM-Based Long-Term In-Vial Monitoring System for Drosophila Larvae.

作者信息

Berh Dimitri, Risse Benjamin, Michels Tim, Otto Nils, Klambt Christian

出版信息

IEEE Trans Biomed Eng. 2017 Aug;64(8):1862-1874. doi: 10.1109/TBME.2016.2628203. Epub 2016 Nov 11.

DOI:10.1109/TBME.2016.2628203
PMID:28113288
Abstract

Drosophila larvae are an insightful model and the automated analysis of their behavior is an integral readout in behavioral biology. Current tracking systems, however, entail a disturbance of the animals, are labor-intensive, and cannot be easily used for long-term monitoring purposes. Here, we present a novel monitoring system for Drosophila larvae, which allows us to analyze the animals in cylindrical culture vials. By utilizing the frustrated total internal reflection in combination with a multi-camera/microcomputer setup, we image the complete housing vial surface and, thus, the larvae for days. We introduce a calibration scheme to stitch the images from the multi-camera system and unfold arbitrary cylindrical surfaces to support different vials. As a result, imaging and analysis of a whole population can be done implicitly. For the first time, this allows us to extract long-term activity quantities of larvae without disturbing the animals. We demonstrate the capabilities of this new setup by automatically quantifying the activity of multiple larvae moving in a vial. The accuracy of the system and the spatio-temporal resolution are sufficient to obtain motion trajectories and higher level features, such as body bending. This new setup can be used for in-vial activity monitoring and behavioral analysis and is capable of gathering millions of data points without both disturbing the animals and increasing labor time. In total, we have analyzed 107 671 frames resulting in 8650 trajectories, which are longer than 30 s, and obtained more than 4.2 × 10 measurements.

摘要

果蝇幼虫是一种很有洞察力的模型,对其行为进行自动化分析是行为生物学中不可或缺的一项指标。然而,目前的追踪系统会对动物造成干扰,劳动强度大,且不易用于长期监测目的。在此,我们提出一种用于果蝇幼虫的新型监测系统,它能让我们在圆柱形培养管中对果蝇进行分析。通过利用受抑全内反射并结合多摄像头/微型计算机设置,我们可以对整个培养管表面成像,从而对幼虫进行长达数天的成像。我们引入了一种校准方案,用于拼接来自多摄像头系统的图像,并展开任意圆柱形表面以适配不同的培养管。这样一来,就可以对整个群体进行隐式成像和分析。首次实现了在不干扰动物的情况下提取幼虫的长期活动量。我们通过自动量化在培养管中移动的多个幼虫的活动,展示了这种新装置的能力。该系统的精度和时空分辨率足以获取运动轨迹和更高层次的特征,如身体弯曲。这种新装置可用于管内活动监测和行为分析,能够在不干扰动物且不增加劳动时间的情况下收集数百万个数据点。我们总共分析了107671帧图像,得到了8650条时长超过30秒的轨迹,并获得了超过4.2×10次测量结果。

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