Data from: Elementary sensory-motor transformations underlying olfactory navigation in walking fruit flies
Álvarez-Salvado, Efrén, New York University Langone Medical Center
Licata, Angela M., New York University Langone Medical Center
Connor, Erin G., University of Colorado Boulder
McHugh, Margaret K., University of Colorado Boulder
King, Benjamin M.N., New York University Langone Medical Center
Stavropoulos, Nicholas, New York University Langone Medical Center
Victor, Jonathan D., Institute for Computational Biomedicine, Weill Cornell Medical College, New York, United States
Crimaldi, John P., University of Colorado Boulder
Nagel, Katherine I., New York University Langone Medical Center
King, Benjamin MN, New York University Langone Medical Center
Published Jul 31, 2019 on Dryad.
Cite this dataset
Álvarez-Salvado, Efrén et al. (2019). Data from: Elementary sensory-motor transformations underlying olfactory navigation in walking fruit flies [Dataset]. Dryad. https://doi.org/10.5061/dryad.g27mq71
Odor attraction in walking Drosophila melanogaster is commonly used to relate neural function to behavior, but the algorithms underlying attraction are unclear. Here we develop a high-throughput assay to measure olfactory behavior in response to well-controlled sensory stimuli. We show that odor evokes two behaviors: an upwind run during odor (ON response), and a local search at odor offset (OFF response). Wind orientation requires antennal mechanoreceptors, but search is driven solely by odor. Using dynamic odor stimuli, we measure the dependence of these two behaviors on odor intensity and history. Based on these data, we develop a navigation model that recapitulates the behavior of flies in our apparatus, and generates realistic trajectories when run in a turbulent boundary layer plume. The ability to parse olfactory navigation into quantifiable elementary sensori-motor transformations provides a foundation for dissecting neural circuits that govern olfactory behavior.