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Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources—such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures—antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.

To navigate towards a food source, animals must frequently combine odor cues, that tell them what sources are useful, with spatial cues such as wind direction that tell them where the odor can be found. Previous studies have identified wind-direction inputs that provide spatial information to the Drosophila navigation center, but olfactory inputs to this structure have not been functionally characterized. Here we use a high-throughput behavioral screen to identify a pathway linking olfactory centers to a part of the navigation center called the fan-shaped body (FB). We show that neurons throughout this pathway promote upwind movement, but encode odor independent of wind direction. We identify a type of FB local neuron that receives input from both wind-encoding and odor-encoding pathways, integrates these cues, and drives turning behavior. Based on connectome data, we develop a computational model that shows how the architecture of the FB enables odor input to flexibly gate behavioral responses to wind direction. Our work supports a model in which spatial and non-spatial information enter the FB through anatomically distinct pathways, and are integrated in FB local neurons to promote context-appropriate navigation behaviors.