Open Source Tracking and Analysis of Adult Drosophila Locomotion in Buridan's Paradigm with and without Visual Targets

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.