Valente Dan, Golani Ilan, Mitra Partha P
Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.
PLoS One. 2007 Oct 24;2(10):e1083. doi: 10.1371/journal.pone.0001083.
Obtaining a complete phenotypic characterization of a freely moving organism is a difficult task, yet such a description is desired in many neuroethological studies. Many metrics currently used in the literature to describe locomotor and exploratory behavior are typically based on average quantities or subjectively chosen spatial and temporal thresholds. All of these measures are relatively coarse-grained in the time domain. It is advantageous, however, to employ metrics based on the entire trajectory that an organism takes while exploring its environment.
METHODOLOGY/PRINCIPAL FINDINGS: To characterize the locomotor behavior of Drosophila melanogaster, we used a video tracking system to record the trajectory of a single fly walking in a circular open field arena. The fly was tracked for two hours. Here, we present techniques with which to analyze the motion of the fly in this paradigm, and we discuss the methods of calculation. The measures we introduce are based on spatial and temporal probability distributions and utilize the entire time-series trajectory of the fly, thus emphasizing the dynamic nature of locomotor behavior. Marginal and joint probability distributions of speed, position, segment duration, path curvature, and reorientation angle are examined and related to the observed behavior.
CONCLUSIONS/SIGNIFICANCE: The measures discussed in this paper provide a detailed profile of the behavior of a single fly and highlight the interaction of the fly with the environment. Such measures may serve as useful tools in any behavioral study in which the movement of a fly is an important variable and can be incorporated easily into many setups, facilitating high-throughput phenotypic characterization.
获取自由活动生物体的完整表型特征是一项艰巨的任务,但在许多神经行为学研究中都需要这样的描述。目前文献中用于描述运动和探索行为的许多指标通常基于平均量或主观选择的空间和时间阈值。所有这些测量在时间域上都相对粗糙。然而,采用基于生物体在探索其环境时所采取的整个轨迹的指标是有利的。
方法/主要发现:为了表征黑腹果蝇的运动行为,我们使用视频跟踪系统记录了一只果蝇在圆形开放场地上行走的轨迹。对这只果蝇进行了两小时的跟踪。在这里,我们展示了分析该范式下果蝇运动的技术,并讨论了计算方法。我们引入的测量基于空间和时间概率分布,并利用果蝇的整个时间序列轨迹,从而强调了运动行为的动态性质。研究了速度、位置、节段持续时间、路径曲率和重新定向角度的边缘和联合概率分布,并将其与观察到的行为相关联。
结论/意义:本文讨论的测量提供了单个果蝇行为的详细概况,并突出了果蝇与环境的相互作用。这些测量可作为任何行为研究中的有用工具,在这些研究中果蝇的运动是一个重要变量,并且可以很容易地纳入许多设置中,便于进行高通量表型特征分析。