Fly navigational responses exploit plume-specific odor motion and gradient cues.

Odor cues guide animals to food and mates. Different environmental conditions can create differently patterned odor plumes, making navigation more challenging. Prior work has shown that animals turn upwind when they detect odor and cast crosswind when they lose it. Animals with bilateral olfactory sensors can also detect directional odor cues, such as odor gradient and odor motion. It remains unknown how animals use these two directional odor cues to guide crosswind navigation in odor plumes with distinct statistics. We investigated this problem theoretically and experimentally. Here, we show that these directional odor cues provide complementary information for navigation in different plume environments. We numerically analyzed experimentally generated plumes to show that odor gradient cues are more informative about crosswind directions in a smooth odor plume, while odor motion cues are more informative in a complex plume. Neural networks trained to optimize crosswind turning converged to distinctive network structures that are tuned to odor gradient cues in a smooth plume and to odor motion cues in a complex one. These trained networks improved the performance of artificial agents navigating plume environments that match the training environment. Last, we recorded