2012年8月10日 訊 /生物谷BIOON/ --近日,，來自德國柏林自由大學(xué)和西班牙基因組研究中心的研究者設(shè)計(jì)出了一款開放源的軟件，其可以在行為實(shí)驗(yàn)中跟蹤果蠅及它們幼蟲的足跡,，從而理解人類大腦決策的制定以及神經(jīng)系統(tǒng)的相關(guān)功能,，相關(guān)研究成果刊登在了國際雜志PLoS One上。
此前,，許多科學(xué)家依賴于昂貴的商業(yè)軟件來研究果蠅成體和幼蟲的行為,；如今研究者開發(fā)出了這款新型軟件，這款軟件寫入了簡單的編程語言,，其可以促進(jìn)科學(xué)家來研究果蠅的行為,。果蠅是一種很好的研究大腦功能的模型，通過仔細(xì)觀察果蠅是否左轉(zhuǎn)還是右轉(zhuǎn),，我們希望更深入地理解人類如何進(jìn)行決策制定,。
這款新型軟件工具可以允許研究者不僅僅提高研究結(jié)果的準(zhǔn)確率，以及開發(fā)出新的分析方法,。研究者表示,，他們很希望看到同行使用這款軟件來幫助其進(jìn)行科研。下一步研究者將使得軟件數(shù)據(jù)在線可以獲取,，而且可以自動化分析,。最終研究者希望包含不同實(shí)驗(yàn)的模板可以轉(zhuǎn)化成電腦可讀的格式，比如3D打印機(jī)可以重新創(chuàng)建精確的實(shí)驗(yàn)數(shù)據(jù)等,。
最后,，研究者Bjom表示，我們希望開發(fā)出最普通和便宜的軟件,，供任何人來進(jìn)行科研實(shí)驗(yàn),。（生物谷Bioon.com）
編譯自：Tracking Fruit Flies to Understand the Function of the Nervous System
doi:10.1371/journal.pone.0041642
PMC:
PMID:
Automated Tracking of Animal Posture and Movement during Exploration and Sensory Orientation Behaviors
Alex Gomez-Marin1*, Nicolas Partoune1,2, Greg J. Stephens3, Matthieu Louis1*
Background The nervous functions of an organism are primarily reflected in the behavior it is capable of. Measuring behavior quantitatively, at high-resolution and in an automated fashion provides valuable information about the underlying neural circuit computation. Accordingly, computer-vision applications for animal tracking are becoming a key complementary toolkit to genetic, molecular and electrophysiological characterization in systems neuroscience. Methodology/Principal Findings We present Sensory Orientation Software (SOS) to measure behavior and infer sensory experience correlates. SOS is a simple and versatile system to track body posture and motion of single animals in two-dimensional environments. In the presence of a sensory landscape, tracking the trajectory of the animal's sensors and its postural evolution provides a quantitative framework to study sensorimotor integration. To illustrate the utility of SOS, we examine the orientation behavior of fruit fly larvae in response to odor, temperature and light gradients. We show that SOS is suitable to carry out high-resolution behavioral tracking for a wide range of organisms including flatworms, fishes and mice. Conclusions/Significance Our work contributes to the growing repertoire of behavioral analysis tools for collecting rich and fine-grained data to draw and test hypothesis about the functioning of the nervous system. By providing open-access to our code and documenting the software design, we aim to encourage the adaptation of SOS by a wide community of non-specialists to their particular model organism and questions of interest.
doi:10.1371/journal.pone.0042247
PMC:
PMID:
Open Source Tracking and Analysis of Adult Drosophila Locomotion in Buridan's Paradigm with and without Visual Targets
Julien Colomb1*, Lutz Reiter1, Jedrzej Blaszkiewicz1, Jan Wessnitzer2, Bjoern Brembs1,3
Background Insects have been among the most widely used model systems for studying the control of locomotion by nervous systems. In Drosophila, we implemented a simple test for locomotion: in Buridan's paradigm, flies walk back and forth between two inaccessible visual targets [1]. Until today, the lack of easily accessible tools for tracking the fly position and analyzing its trajectory has probably contributed to the slow acceptance of Buridan's paradigm. Methodology/Principal Findings We present here a package of open source software designed to track a single animal walking in a homogenous environment (Buritrack) and to analyze its trajectory. The Centroid Trajectory Analysis (CeTrAn) software is coded in the open source statistics project R. It extracts eleven metrics and includes correlation analyses and a Principal Components Analysis (PCA). It was designed to be easily customized to personal requirements. In combination with inexpensive hardware, these tools can readily be used for teaching and research purposes. We demonstrate the capabilities of our package by measuring the locomotor behavior of adult Drosophila melanogaster (whose wings were clipped), either in the presence or in the absence of visual targets, and comparing the latter to different computer-generated data. The analysis of the trajectories confirms that flies are centrophobic and shows that inaccessible visual targets can alter the orientation of the flies without changing their overall patterns of activity. Conclusions/Significance Using computer generated data, the analysis software was tested, and chance values for some metrics (as well as chance value for their correlation) were set. Our results prompt the hypothesis that fixation behavior is observed only if negative phototaxis can overcome the propensity of the flies to avoid the center of the platform. Together with our companion paper, we provide new tools to promote Open Science as well as the collection and analysis of digital behavioral data.
