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First published online March 27, 2009
Journal of Experimental Biology 212, 1120-1130 (2009)
Published by The Company of Biologists 2009
doi: 10.1242/jeb.020768
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Visual control of flight speed in Drosophila melanogaster

Steven N. Fry1,2,*, Nicola Rohrseitz1, Andrew D. Straw3 and Michael H. Dickinson3

1 Institute of Neuroinformatics, University of Zürich and ETH Zürich, Switzerland
2 Institute of Robotics and Intelligent Systems, ETH Zürich, Switzerland
3 Bioengineering, California Institute of Technology, MC 138-78, Pasadena, CA 91125, USA

* Author for correspondence (e-mail: steven{at}ini.ch)

Accepted 21 January 2009

Flight control in insects depends on self-induced image motion (optic flow), which the visual system must process to generate appropriate corrective steering maneuvers. Classic experiments in tethered insects applied rigorous system identification techniques for the analysis of turning reactions in the presence of rotating pattern stimuli delivered in open-loop. However, the functional relevance of these measurements for visual free-flight control remains equivocal due to the largely unknown effects of the highly constrained experimental conditions. To perform a systems analysis of the visual flight speed response under free-flight conditions, we implemented a `one-parameter open-loop' paradigm using `TrackFly' in a wind tunnel equipped with real-time tracking and virtual reality display technology. Upwind flying flies were stimulated with sine gratings of varying temporal and spatial frequencies, and the resulting speed responses were measured from the resulting flight speed reactions. To control flight speed, the visual system of the fruit fly extracts linear pattern velocity robustly over a broad range of spatio–temporal frequencies. The speed signal is used for a proportional control of flight speed within locomotor limits. The extraction of pattern velocity over a broad spatio–temporal frequency range may require more sophisticated motion processing mechanisms than those identified in flies so far. In Drosophila, the neuromotor pathways underlying flight speed control may be suitably explored by applying advanced genetic techniques, for which our data can serve as a baseline. Finally, the high-level control principles identified in the fly can be meaningfully transferred into a robotic context, such as for the robust and efficient control of autonomous flying micro air vehicles.

Key words: Drosophila, flight control, behavior, vision


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© The Company of Biologists Ltd 2009