The compound eye of insects imposes a tradeoff between resolution and sensitivity, which should exacerbate with diminishing eye size. Tiny lenses are thought to deliver poor acuity because of diffraction; nevertheless, miniature insects have visual systems that allow a myriad of lifestyles. Here, we investigate whether size constraints result in an archetypal eye design shared between miniature dipterans by comparing the visual performance of the fruit fly Drosophila and the killer fly Coenosia. These closely related species have neural superposition eyes and similar body lengths (3 to 4 mm), but Coenosia is a diurnal aerial predator, whereas slow-flying Drosophila is most active at dawn and dusk. Using in vivo intracellular recordings and EM, we report unique adaptations in the form and function of their photoreceptors that are reflective of their distinct lifestyles. We find that although these species have similar lenses and optical properties, Coenosia photoreceptors have three-to fourfold higher spatial resolution and rate of information transfer than Drosophila. The higher performance in Coenosia mostly results from dramatically diminished light sensors, or rhabdomeres, which reduce pixel size and optical cross-talk between photoreceptors and incorporate accelerated phototransduction reactions. Furthermore, we identify local specializations in the Coenosia eye, consistent with an acute zone and its predatory lifestyle. These results demonstrate how the flexible architecture of miniature compound eyes can evolve to match information processing with ecological demands.vision | predatory behavior | invertebrate | evolution T he design of a compound eye depends on the limits imposed by body size, architectural properties of the eye, visual task, and habitat, all of which affect its ability to resolve environmental light patterns (1-3). Typically, compound eyes are roughly spherical in shape, sectored into arrays of lens-capped sampling units, named ommatidia, which accept light from narrow angles (3), determining their sampling resolution (4). Although the eye's sampling resolution can improve when its lenses shrink, their projected image blurs more because of diffraction (5). The optimal lens diameter, which is expected when these two limits nearly meet, scales with the square root of the eye size across many insect species (5), implying high resolution as their design objective. However, smaller lenses collect less light, reducing the signal-tonoise ratio (SNR) of the sampled image (4). Although the lenses perform light collection, the focal length of the lens and the diameter of the light guides, or rhabdomeres, finally determine the pixel size (6). In combination, lens diameter, rhabdomere width, and focal length impose a tradeoff between spatial resolution and sensitivity (intensity resolution), which is thought to be further aggravated the smaller the eyes (3,7,8).Ultimately, because the demands for pattern recognition differ greatly for different visual tasks and habitats (9), the selected eye design sh...

SummaryOur visual system allows us to rapidly identify and intercept a moving object. When this object is far away, we base the trajectory on the target’s location relative to an external frame of reference [1]. This process forms the basis for the constant bearing angle (CBA) model, a reactive strategy that ensures interception since the bearing angle, formed between the line joining pursuer and target (called the range vector) and an external reference line, is held constant [2, 3, 4]. The CBA model may be a fundamental and widespread strategy, as it is also known to explain the interception trajectories of bats and fish [5, 6]. Here, we show that the aerial attack of the tiny robber fly Holcocephala fusca is consistent with the CBA model. In addition, Holcocephala fusca displays a novel proactive strategy, termed “lock-on” phase, embedded with the later part of the flight. We found the object detection threshold for this species to be 0.13°, enabled by an extremely specialized, forward pointing fovea (∼5 ommatidia wide, interommatidial angle Δφ = 0.28°, photoreceptor acceptance angle Δρ = 0.27°). This study furthers our understanding of the accurate performance that a miniature brain can achieve in highly demanding sensorimotor tasks and suggests the presence of equivalent mechanisms for target interception across a wide range of taxa.Video Abstract

Three-dimensional (3D) bioimaging, visualization and data analysis are in strong need of powerful 3D exploration techniques. We develop virtual finger (VF) to generate 3D curves, points and regions-of-interest in the 3D space of a volumetric image with a single finger operation, such as a computer mouse stroke, or click or zoom from the 2D-projection plane of an image as visualized with a computer. VF provides efficient methods for acquisition, visualization and analysis of 3D images for roundworm, fruitfly, dragonfly, mouse, rat and human. Specifically, VF enables instant 3D optical zoom-in imaging, 3D free-form optical microsurgery, and 3D visualization and annotation of terabytes of whole-brain image volumes. VF also leads to orders of magnitude better efficiency of automated 3D reconstruction of neurons and similar biostructures over our previous systems. We use VF to generate from images of 1,107 Drosophila GAL4 lines a projectome of a Drosophila brain.

Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair with a 95% success rate. In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not. Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this information is relayed from the brain to the wing motor centers in population vector form.vision | invertebrate | predatory behavior | electrophysiology | confocal microscopy D ragonflies continuously track their prey (1) during short predatory flights (∼200-500 ms) (1-3) by keeping the image of the moving prey on the specialized dorsal area of their eyes (1). If the prey image drifts on the retina, compensatory motor signals sent to the wings adjust the dragonfly body position to bring the prey image back. This process allows a dragonfly to visually track the prey by locking on to it, a process also named fixation (4).The ability to fixate on a moving target is a common feature among most predatory animals. Once a pursuer's eyes are fixated on the prey, it can aim toward the current or the future prey location. The first choice results in classical pursuit, whereas the second one yields interception. Dragonflies are thought to intercept their prey by keeping a constant bearing to their target. This strategy is also used by other species, e.g., a human catching a ball (5, 6), but the nervous system of dragonflies presents a favorable substrate for studying the neural basis of this behavior. This ancient prey-targeting system is tractable and tuned for extreme performance, as evidenced by the accuracy (around 95%) (1, 2) and speed at which it functions.We aimed to understand the information sent to the wings when a target moves across the dragonfly visual field. In particular, we have tested whether the population vector algorithm can successfully decode the directional component of the descending information. The population vector is the weighted sum activity of an ensemble of neurons with directional tuning. It was first shown to predict the direction of an upcoming arm movement in monkeys (7,8). Since then, the population vector algorithm has described successfully the directional responses to mechanical stimulation in several invertebrate species (9-12). The dragonfly predatory flight provides a challenge for a reliable vector code. Not only are these animals highly maneuverable, with independent control of the fore and hind wings (13) a...