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Nocturnal hawkmoths are known for impressive visually guided behaviours in dim light, such as hovering while feeding from nectar-bearing flowers. This requires tight visual feedback to estimate and counter relative motion. Discrimination of low velocities, as required for stable hovering flight, is fundamentally limited by spatial resolution, yet in the evolution of eyes for nocturnal vision, maintenance of high spatial acuity compromises absolute sensitivity. To investigate these trade-offs, we compared responses of wide-field motion-sensitive neurons in three species of hawkmoth: Manduca sexta (a crepuscular hoverer), Deilephila elpenor (a fully nocturnal hoverer) and Acherontia atropos (a fully nocturnal hawkmoth that does not hover as it feeds uniquely from honey in bees' nests). We show that despite smaller eyes, the motion pathway of D. elpenor is tuned to higher spatial frequencies and lower temporal frequencies than A. atropos, consistent with D. elpenor's need to detect low velocities for hovering. Acherontia atropos, however, presumably evolved low-light sensitivity without sacrificing temporal acuity. Manduca sexta, active at higher light levels, is tuned to the highest spatial frequencies of the three and temporal frequencies comparable with A. atropos. This yields similar tuning to low velocities as in D. elpenor, but with the advantage of shorter neural delays in processing motion.

SUMMARYFor a small flying insect, correcting unplanned course perturbations is essential for navigating through the world. Visual course control relies on estimating optic flow patterns which, in flies, are encoded by interneurons of the third optic ganglion. However, the rules that translate optic flow into flight motor commands remain poorly understood. Here, we measured the temporal dynamics of optomotor responses in tethered flies to optic flow fields about three cardinal axes. For each condition, we used white noise analysis to determine the optimal linear filters linking optic flow to the sum and difference of left and right wing beat amplitudes. The estimated filters indicate that flies react very quickly to perturbations of the motion field, with pure delays in the order of ~20 ms and time-to-peak of ~100 ms. By convolution the filters also predict responses to arbitrary stimulus sequences, accounting for over half the variance in 5 of our 6 stimulus types, demonstrating the approximate linearity of the system with respect to optic flow variables. In the remaining case of yaw optic flow we improved predictability by measuring individual flies, which also allowed us to analyze the variability of optomotor responses within a population. Finally, the linear filters at least partly explain the optomotor responses to superimposed and decomposed compound flow fields. Supplementary material available online at

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