M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice

IF 3.6 2区 生物学 PLoS Computational Biology Pub Date : 2016-09-01 DOI:10.1371/journal.pcbi.1005115
Sheldon L. Reeves, Kelsey E. Fleming, Lin Zhang, A. Scimemi
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引用次数: 21

Abstract

Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies.
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M-Track:一种自动检测小鼠梳理轨迹的新软件
梳理毛发是一种复杂而强健的先天行为,大多数脊椎动物都有这种行为。在老鼠身上,梳理毛发是由一系列固定模式的抚摸组成的,这些抚摸沿着身体的尾巴轴进行。每次梳理毛发的频率和持续时间对压力水平、社会互动和药物操作的变化很敏感,因此被用于行为研究,以深入了解控制运动执行和焦虑的大脑区域的功能。分析梳理毛发的传统方法依赖于手动对每次梳理毛发的开始时间和持续时间进行评分,并且通常是在压力暴露引发的梳理毛发的情况下进行的,这可能并不完全代表自由行为小鼠的自发梳理毛发。这种类型的分析是耗时的,并且提供的关于梳理行为更精细方面的信息有限,这对于理解老鼠的运动刻板印象和双边协调很重要。目前可用的商业和免费视频跟踪软件允许自动跟踪老鼠的整个身体或它的头和尾巴,而不是单个前爪。在这里,我们描述了一个简单的实验装置和一个名为M-Track的新颖的开源代码,用于同时跟踪多个自由行为的小鼠在自发梳理时单个前爪的运动。这个工具箱提供了一个简单的平台来执行轨迹分析的前爪运动在不同的梳理事件。通过M-track,我们发现在C57BL/6野生型小鼠中,左右前爪的速度和双边协调在不同的梳理过程中保持不变。应激暴露导致前爪梳理轨迹的长度显著增加。M-Track提供了一个有价值和用户友好的界面,以简化生物医学研究中自发梳理的分析。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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