Neural Summation in the Hawkmoth Visual System Extends the Limits of Vision in Dim Light

Head movements quadruple the range of speeds encoded by the insect motion vision system in hawkmoths

Flying insects use compensatory head movements to stabilize gaze. Like other optokinetic responses, these movements can reduce image displacement, motion and misalignment, and simplify the optic flow field. Because gaze is imperfectly stabilized in insects, we hypothesized that compensatory head movements serve to extend the range of velocities of self-motion that the visual system encodes. We tested this by measuring head movements in hawkmoths Hyles lineata responding to full-field visual stimuli of differing oscillation amplitudes, oscillation frequencies and spatial frequencies. We used frequency-domain system identification techniques to characterize the head's roll response, and simulated how this would have affected the output of the motion vision system, modelled as a computational array of Reichardt detectors. The moths' head movements were modulated to allow encoding of both fast and slow self-motion, effectively quadrupling the working range of the visual system for flight control. By using its own output to drive compensatory head movements, the motion vision system thereby works as an adaptive sensor, which will be especially beneficial in nocturnal species with inherently slow vision. Studies of the ecology of motion vision must therefore consider the tuning of motion-sensitive interneurons in the context of the closed-loop systems in which they function.

Generation and Evolution of Neural Cell Types and Circuits: Insights from the Drosophila Visual System

The Drosophila visual system has become a premier model for probing how neural diversity is generated during development. Recent work has provided deeper insight into the elaborate mechanisms that control the range of types and numbers of neurons produced, which neurons survive, and how they interact. These processes drive visual function and influence behavioral preferences. Other studies are beginning to provide insight into how neuronal diversity evolved in insects by adding new cell types and modifying neural circuits. Some of the most powerful comparisons have been those made to the Drosophila visual system, where a deeper understanding of molecular mechanisms allows for the generation of hypotheses about the evolution of neural anatomy and function. The evolution of new neural types contributes additional complexity to the brain and poses intriguing questions about how new neurons interact with existing circuitry. We explore how such individual changes in a variety of species might play a role over evolutionary timescales. Lessons learned from the fly visual system apply to other neural systems, including the fly central brain, where decisions are made and memories are stored.

High contrast sensitivity for visually guided flight control in bumblebees

Many insects rely on vision to find food, to return to their nest and to carefully control their flight between these two locations. The amount of information available to support these tasks is, in part, dictated by the spatial resolution and contrast sensitivity of their visual systems. Here, we investigate the absolute limits of these visual properties for visually guided position and speed control in Bombus terrestris. Our results indicate that the limit of spatial vision in the translational motion detection system of B. terrestris lies at 0.21 cycles deg⁻¹ with a peak contrast sensitivity of at least 33. In the perspective of earlier findings, these results indicate that bumblebees have higher contrast sensitivity in the motion detection system underlying position control than in their object discrimination system. This suggests that bumblebees, and most likely also other insects, have different visual thresholds depending on the behavioral context.

Microsaccadic sampling of moving image information provides Drosophila hyperacute vision

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors’ encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes’ optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements.

Fruit flies have five eyes: two large compound eyes which support vision, plus three smaller single lens eyes which are used for navigation. Each compound eye monitors 180° of space and consists of roughly 750 units, each containing eight light-sensitive cells called photoreceptors. This relatively wide spacing of photoreceptors is thought to limit the sharpness, or acuity, of vision in fruit flies. The area of the human retina (the light-sensitive surface at back of our eyes) that generates our sharpest vision contains photoreceptors that are 500 times more densely packed.

Despite their differing designs, human and fruit fly eyes work via the same general principles. If we, or a fruit fly, were to hold our gaze completely steady, the world would gradually fade from view as the eye adapted to the unchanging visual stimulus. To ensure this does not happen, animals continuously make rapid, automatic eye movements called microsaccades. These refresh the image on the retina and prevent it from fading. Yet it is not known why do they not also cause blurred vision.

Standard accounts of vision assume that the retina and the brain perform most of the information processing required, with photoreceptors simply detecting how much light enters the eye. However, Juusola, Dau, Song et al. now challenge this idea by showing that photoreceptors are specially adapted to detect the fluctuating patterns of light that enter the eye as a result of microsaccades. Moreover, fruit fly eyes resolve small moving objects far better than would be predicted based on the spacing of their photoreceptors.

The discovery that photoreceptors are well adapted to deal with eye movements changes our understanding of insect vision. The findings also disprove the 100-year-old dogma that the spacing of photoreceptors limits the sharpness of vision in compound eyes. Further studies are required to determine whether photoreceptors in the retinas of other animals, including humans, have similar properties.

How a fly photoreceptor samples light information in time

A photoreceptor's information capture is constrained by the structure and function of its light‐sensitive parts. Specifically, in a fly photoreceptor, this limit is set by the number of its photon sampling units (microvilli), constituting its light sensor (the rhabdomere), and the speed and recoverability of their phototransduction reactions. In this review, using an insightful constructionist viewpoint of a fly photoreceptor being an ‘imperfect’ photon counting machine, we explain how these constraints give rise to adaptive quantal information sampling in time, which maximises information in responses to salient light changes while antialiasing visual signals. Interestingly, such sampling innately determines also why photoreceptors extract more information, and more economically, from naturalistic light contrast changes than Gaussian white‐noise stimuli, and we explicate why this is so. Our main message is that stochasticity in quantal information sampling is less noise and more processing, representing an ‘evolutionary adaptation’ to generate a reliable neural estimate of the variable world.

Differential investment in visual and olfactory brain areas reflects behavioural choices in hawk moths

Nervous tissue is one of the most metabolically expensive animal tissues, thus evolutionary investments that result in enlarged brain regions should also result in improved behavioural performance. Indeed, large-scale comparative studies in vertebrates and invertebrates have successfully linked differences in brain anatomy to differences in ecology and behaviour, but their precision can be limited by the detail of the anatomical measurements, or by only measuring behaviour indirectly. Therefore, detailed case studies are valuable complements to these investigations, and have provided important evidence linking brain structure to function in a range of higher-order behavioural traits, such as foraging experience or aggressive behaviour. Here, we show that differences in the size of both lower and higher-order sensory brain areas reflect differences in the relative importance of these senses in the foraging choices of hawk moths, as suggested by previous anatomical work in Lepidopterans. To this end we combined anatomical and behavioural quantifications of the relative importance of vision and olfaction in two closely related hawk moth species. We conclude that differences in sensory brain volume in these hawk moths can indeed be interpreted as differences in the importance of these senses for the animal’s behaviour.

Innate preference and learning of colour in the male cotton bollworm Helicoverpa armigera

We investigated the ability of colour discrimination and learning in male adults of nocturnal cotton bollworm moth, Helicoverpa armigera, under a dim light condition. The naïve moths preferred blue and discriminated the innately preferred blue from several shades of grey indicating that the moths have colour vision. After being trained for 2 days to take nectar at yellow, an innately non-preferred colour, moths learned to select yellow over blue. The choice distribution between yellow and blue changed significantly from that of naïve moths. However, the dual choice distribution of the trained moths was not significantly biased to yellow: the preference for blue is robust. We also tried to train moths to grey, which was not successful. The limited ability to learn colours suggests that H. armigera may not strongly rely on colours when searching for flowers in the field, although they have basic property of colour vision.