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arXiv · 1210.4485

Leg-tracking and automated behavioral classification in Drosophila

Jamey Kain·Chris Stokes·Quentin Gaudry·Xiangzhi Song·James Foley·Rachel Wilson·Benjamin de Bivort
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Abstract

Here we present the first method for tracking each leg of a fruit fly behaving spontaneously upon a trackball, in real time. Legs were tracked with infrared-fluorescent dye invisible to the fly, and compatible with two-photon microscopy and controlled visual stimuli. We developed machine learning classifiers to identify instances of numerous behavioral features (e.g. walking, turning, grooming) thus producing the highest resolution ethological profiles for individual flies.

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Jamey Kain, Chris Stokes, Quentin Gaudry, Xiangzhi Song, James Foley, Rachel Wilson, Benjamin de Bivort. 2012-10-16. Leg-tracking and automated behavioral classification in Drosophila. https://doi.org/10.1038/ncomms2908

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