Summary All moving animals, including flies [1–3], sharks [4], and humans [5], experience a dynamic sensory landscape that is a function of both their trajectory through space and the distribution of stimuli in the environment. This is particularly apparent for mosquitoes, which use a combination of olfactory, visual, and thermal cues to locate hosts [6–10]. Mosquitoes are thought to detect suitable hosts by the presence of a sparse CO2 plume, which they track by surging upwind and casting crosswind [11]. Upon approach, local cues such as heat and skin volatiles help them identify a landing site [12–15]. Recent evidence suggests that thermal attraction is gated by the presence of CO2 [6], although this conclusion was based experiments in which the actual flight trajectories of the animals were unknown and visual cues were not studied. Using a 3-dimensional tracking system we show that rather than gating heat sensing, the detection of CO2 actually activates a strong attraction to visual features. This visual reflex guides the mosquitoes to potential hosts where they are close enough to detect thermal cues. By experimentally decoupling the olfactory, visual, and thermal cues, we show that the motor reactions to these stimuli are independently controlled. Given that humans become visible to mosquitoes at a distance of 5–15 m [16], visual cues play a critical intermediate role in host localization by coupling long-range plume tracking to behaviors that require short-range cues. Rather than direct neural coupling, the separate sensory-motor reflexes are linked as a result of the interaction between the animal’s reactions and the spatial structure of the stimuli in the environment.

Due to plume structure and sensory-motor delays, a fly's olfactory experience during foraging flights consists of short bursts of odor stimulation. As a consequence, delays in the onset of crosswind casting and the increased attraction to visual features are necessary behavioral components for efficiently locating an odor source. Our results provide a quantitative behavioral background for elucidating the neural basis of plume tracking using genetic and physiological approaches.

SUMMARYLanding behavior is one of the most critical, yet least studied, aspects of insect flight. In order to land safely, an insect must recognize a visual feature, navigate towards it, decelerate, and extend its legs in preparation for touchdown. Although previous studies have focused on the visual stimuli that trigger these different components, the complete sequence has not been systematically studied in a free-flying animal. Using a real-time 3D tracking system in conjunction with high speed digital imaging, we were able to capture the landing sequences of fruit flies (Drosophila melanogaster) from the moment they first steered toward a visual target, to the point of touchdown. This analysis was made possible by a custom-built feedback system that actively maintained the fly in the focus of the high speed camera. The results suggest that landing is composed of three distinct behavioral modules. First, a fly actively turns towards a stationary target via a directed body saccade. Next, it begins to decelerate at a point determined by both the size of the visual target and its rate of expansion on the retina. Finally, the fly extends its legs when the visual target reaches a threshold retinal size of approximately 60deg. Our data also let us compare landing sequences with flight trajectories that, although initially directed toward a visual target, did not result in landing. In these ʻfly-byʼ trajectories, flies steer toward the target but then exhibit a targeted aversive saccade when the target subtends a retinal size of approximately 33deg. Collectively, the results provide insight into the organization of sensorimotor modules that underlie the landing and search behaviors of insects. Supplementary material available online at

No abstract

Vision is arguably the most widely used sensor for position and velocity estimation in animals, and it is increasingly used in robotic systems as well. Many animals use stereopsis and object recognition in order to make a true estimate of distance. For a tiny insect such as a fruit fly or honeybee, however, these methods fall short. Instead, an insect must rely on calculations of optic flow, which can provide a measure of the ratio of velocity to distance, but not either parameter independently. Nevertheless, flies and other insects are adept at landing on a variety of substrates, a behavior that inherently requires some form of distance estimation in order to trigger distance-appropriate motor actions such as deceleration or leg extension. Previous studies have shown that these behaviors are indeed under visual control, raising the question: how does an insect estimate distance solely using optic flow? In this paper we use a nonlinear control theoretic approach to propose a solution for this problem. Our algorithm takes advantage of visually controlled landing trajectories that have been observed in flies and honeybees. Finally, we implement our algorithm, which we term dynamic peering, using a camera mounted to a linear stage to demonstrate its real-world feasibility.

We thank B. Nguyen for mosquito colony maintenance, J. Tuthill and P. Weir for comments and help with the arena experiments, G. Wolff for comments and imaging assistance, and D.

Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advected odor signal into intermittent filaments and puffs. This scenario provides an opportunity to ask how animals use sparse, instantaneous, and stochastic signal encounters to generate goal-oriented behavioral sequences. Here we examined the trajectories of flying fruit flies (Drosophila melanogaster) and mosquitoes (Aedes aegypti) navigating in controlled plumes of attractive odorants. While it is known that mean odor-triggered flight responses are dominated by upwind turns, individual responses are highly variable. We asked whether deviations from mean responses depended on specific features of odor encounters, and found that odor-triggered turns were slightly but significantly modulated by two features of odor encounters. First, encounters with higher concentrations triggered stronger upwind turns. Second, encounters occurring later in a sequence triggered weaker upwind turns. To contextualize the latter history dependence theoretically, we examined trajectories simulated from three normative tracking strategies. We found that neither a purely reactive strategy nor a strategy in which the tracker learned the plume centerline over time captured the observed history dependence. In contrast, “infotaxis”, in which flight decisions maximized expected information gain about source location, exhibited a history dependence aligned in sign with the data, though much larger in magnitude. These findings suggest that while true plume tracking is dominated by a reactive odor response it might also involve a history-dependent modulation of responses consistent with the accumulation of information about a source over multi-encounter timescales. This suggests that short-term memory processes modulating decision sequences may play a role in natural plume tracking.

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.