Visual control of flight speed inDrosophila melanogaster

Author:

Fry Steven N.12,Rohrseitz Nicola1,Straw Andrew D.3,Dickinson Michael H.3

Affiliation:

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

Abstract

SUMMARYFlight 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.

Publisher

The Company of Biologists

Subject

Insect Science,Molecular Biology,Animal Science and Zoology,Aquatic Science,Physiology,Ecology, Evolution, Behavior and Systematics

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