Elementary sensory-motor transformations underlying olfactory navigation in walking fruit flies

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.

行走中的黑腹果蝇（Drosophila melanogaster）的气味吸引行为，常被用于关联神经功能与行为，但该吸引行为背后的算法机制仍不明晰。本研究开发了一种高通量检测方法，用于测量果蝇在精准可控的感觉刺激下的嗅觉行为。研究发现气味可诱发两类行为：气味存在时的逆风行进（开启响应，ON response），以及气味消失时的局部搜寻（关闭响应，OFF response）。逆风定向依赖触角机械感受器，但局部搜寻仅由气味驱动。借助动态气味刺激，我们量化了这两类行为对气味强度与刺激历史的依赖关系。基于上述数据，我们构建了一个导航模型，该模型可重现果蝇在本实验装置中的行为，并在湍流边界层羽流环境中生成符合真实情况的运动轨迹。将嗅觉导航拆解为可量化的基础感觉运动转换单元的能力，为解析调控嗅觉行为的神经环路奠定了基础。