David C. O'Carroll

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

Most of the worlds animals are active in dim light and depend on good vision for the tasks of daily life. Many have evolved visual adaptations that permit a performance superior to that of manmade imaging devices [1]. In insects, a major model visual system, nocturnal species show impressive visual abilities ranging from flight control [2, 3], to color discrimination [4, 5], to navigation using visual landmarks [6-8] or dim celestial compass cues [9, 10]. In addition to optical adaptations that improve their sensitivity in dim light [11], neural summation of light in space and time-which enhances the coarser and slower features of the scene at the expense of noisier finer and faster features-has been suggested to improve sensitivity in theoretical [12-14], anatomical [15-17], and behavioral [18-20] studies. How these summation strategies function neurally is, however, presently unknown. Here, we quantified spatial and temporal summation in the motion vision pathway of a nocturnal hawkmoth. We show that spatial and temporal summation combine supralinearly to substantially increase contrast sensitivity and visual information rate over four decades of light intensity, enabling hawkmoths to see at light levels 100 times dimmer than without summation. Our results reveal how visual motion is calculated neurally in dim light and how spatial and temporal summation improve sensitivity while simultaneously maximizing spatial and temporal resolution, thus extending models of insect motion vision derived predominantly from diurnal flies. Moreover, the summation strategies we have revealed may benefit manmade vision systems optimized for variable light levels [21].

Vision in dim light: Highlights and challenges

On a moonless night or in the depths of the sea, where light levels are many orders of magnitude dimmer than sunlight, animals rely on their visual systems to orient and navigate, to find food and mates and to avoid predators. To see well at such low light levels is far from trivial. The paucity of light means that visual signals generated in the light-sensitive photoreceptors of the retina can easily be drowned in neural noise. Despite this, research over the past 15 years has revealed that nocturnal and deep-sea animals—even very small animals like insects with tiny eyes and brains—can have formidable visual abilities in dim light. The latest research in the field is now beginning to reveal how this visual performance is possible, and in particular which optical and neural strategies have evolved that permit reliable vision in dim light. This flurry of research is rapidly changing our understanding of both the limitations and the capabilities of animals active in very dim light. For instance, while the long-held view was that night vision allows only an impoverished, noisy and monochrome view of the world, we now know that many nocturnal animals see the world more or less in the same manner as their day-active relatives. Many are able to see colour, to use optic flow cues to control flight, and to navigate using learned visual landmarks and celestial cues such as polarized light. Much of our appreciation of the richness of the visual world seen by nocturnal animals has derived primarily from behavioural, anatomical and optical studies. More recently, enormous advances have also been made in understanding the neural basis of this performance in both single cells and circuits of cells from both nocturnal vertebrates (notably mice) and nocturnal invertebrates (notably insects). These studies indicate that the remarkable behavioural performance of these animals in dim light can only partially be explained by what we currently know of the performance of the underlying visual cells. We are thus now at an important point in the field where this gap is closing. It is thus particularly timely that this special issue brings together a unique combination of recent research on deep-sea and nocturnal animals and moreover from a wide spectrum of scientific disciplines, from ecology, evolution and quantitative visual behaviour to cellular electrophysiology, mathematical modelling and molecular biology. This landmark collection of papers is the first to exclusively address the topic of comparative vision in dim light.

Three-dimensional functional human neuronal networks in uncompressed low-density electrospun fiber scaffolds

We demonstrate an artificial three-dimensional (3D) electrical active human neuronal network system, by the growth of brain neural progenitors in highly porous low density electrospun poly-ε-caprolactone (PCL) fiber scaffolds. In neuroscience research cell-based assays are important experimental instruments for studying neuronal function in health and disease. Traditional cell culture at 2D-surfaces induces abnormal cell-cell contacts and network formation. Hence, there is a tremendous need to explore in vivo-resembling 3D neural cell culture approaches. We present an improved electrospinning method for fabrication of scaffolds that promote neuronal differentiation into highly 3D integrated networks, formation of inhibitory and excitatory synapses and extensive neurite growth. Notably, in 3D scaffolds in vivo-resembling intermixed neuronal and glial cell network were formed, whereas in parallel 2D cultures a neuronal cell layer grew separated from an underlying glial cell layer. Hence, the use of the 3D cell assay presented will most likely provide more physiological relevant results.

Computational models for spatiotemporal filtering strategies in insect motion vision at low light levels

We explore a promising new approach to understanding the neural filter mechanisms intermediate in motion processing at low luminance. We carefully account for the known filter properties of early stages of visual processing in a nocturnal moth, and then measured spatiotemporal tuning of higher order neurons. We then use a computational model to identify likely strategies used to reject noisy signals at higher-order stages of motion detection. In so doing, we provide the first description of the spatial and temporal ‘pooling’ filters in motion vision of nocturnal insects.

Visual acuity of the honey bee retina and the limits for feature detection

Visual abilities of the honey bee have been studied for more than 100 years, recently revealing unexpectedly sophisticated cognitive skills rivalling those of vertebrates. However, the physiological limits of the honey bee eye have been largely unaddressed and only studied in an unnatural, dark state. Using a bright display and intracellular recordings, we here systematically investigated the angular sensitivity across the light adapted eye of honey bee foragers. Angular sensitivity is a measure of photoreceptor receptive field size and thus small values indicate higher visual acuity. Our recordings reveal a fronto-ventral acute zone in which angular sensitivity falls below 1.9°, some 30% smaller than previously reported. By measuring receptor noise and responses to moving dark objects, we also obtained direct measures of the smallest features detectable by the retina. In the frontal eye, single photoreceptors respond to objects as small as 0.6° × 0.6°, with >99% reliability. This indicates that honey bee foragers possess significantly better resolution than previously reported or estimated behaviourally, and commonly assumed in modelling of bee acuity.

Higher-order neural processing tunes motion neurons to visual ecology in three species of hawkmoths

To sample information optimally, sensory systems must adapt to the ecological demands of each animal species. These adaptations can occur peripherally, in the anatomical structures of sensory organs and their receptors; and centrally, as higher-order neural processing in the brain. While a rich body of investigations has focused on peripheral adaptations, our understanding is sparse when it comes to central mechanisms. We quantified how peripheral adaptations in the eyes, and central adaptations in the wide-field motion vision system, set the trade-off between resolution and sensitivity in three species of hawkmoths active at very different light levels: nocturnal Deilephila elpenor, crepuscular Manduca sexta, and diurnal Macroglossum stellatarum. Using optical measurements and physiological recordings from the photoreceptors and wide-field motion neurons in the lobula complex, we demonstrate that all three species use spatial and temporal summation to improve visual performance in dim light. The diurnal Macroglossum relies least on summation, but can only see at brighter intensities. Manduca, with large sensitive eyes, relies less on neural summation than the smaller eyed Deilephila, but both species attain similar visual performance at nocturnal light levels. Our results reveal how the visual systems of these three hawkmoth species are intimately matched to their visual ecologies.

Properties of neuronal facilitation that improve target tracking in natural pursuit simulations

Although flying insects have limited visual acuity (approx. 1°) and relatively small brains, many species pursue tiny targets against cluttered backgrounds with high success. Our previous computational model, inspired by electrophysiological recordings from insect ‘small target motion detector’ (STMD) neurons, did not account for several key properties described from the biological system. These include the recent observations of response ‘facilitation’ (a slow build-up of response to targets that move on long, continuous trajectories) and ‘selective attention’, a competitive mechanism that selects one target from alternatives. Here, we present an elaborated STMD-inspired model, implemented in a closed loop target-tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. We test this system against heavily cluttered natural scenes. Inclusion of facilitation not only substantially improves success for even short-duration pursuits, but it also enhances the ability to ‘attend’ to one target in the presence of distracters. Our model predicts optimal facilitation parameters that are static in space and dynamic in time, changing with respect to the amount of background clutter and the intended purpose of the pursuit. Our results provide insights into insect neurophysiology and show the potential of this algorithm for implementation in artificial visual systems and robotic applications.

Performance assessment of an insect-inspired target tracking model in background clutter

Biological visual systems provide excellent examples of robust target detection and tracking mechanisms capable of performing in a wide range of environments. Consequently, they have been sources of inspiration for many artificial vision algorithms. However, testing the robustness of target detection and tracking algorithms is a challenging task due to the diversity of environments for applications of these algorithms. Correlation between image quality metrics and model performance is one way to deal with this problem. Previously we developed a target detection model inspired by physiology of insects and implemented it in a closed loop target tracking algorithm. In the current paper we vary the kinetics of a salience-enhancing element of our algorithm and test its effect on the robustness of our model against different natural images to find the relationship between model performance and background clutter.

The cholinergic pesticide imidacloprid impairs contrast and direction sensitivity in motion detecting neurons of an insect pollinator

Cholinergic pesticides such as the neonicotinoid imidacloprid are the most important insecticides used for plant protection worldwide. In recent decades concerns have been raised about side effects on non-target insect species, including altered foraging behaviour and navigation. Although pollinators rely on visual cues to forage and navigate their environment, the effect of neonicotinoids on visual processing have been largely overlooked. Here we describe a modified electrophysiological setup that allowed recordings of visually evoked responses while perfusing the brain in vivo. Long-lasting recordings from wide-field motion sensitive neurons of the hoverfly pollinator, Eristalis tenax, revealed that sub-lethal exposure to imidacloprid alters their physiological response to motion stimuli. We observed substantially increased spontaneous firing rate, reduced contrast sensitivity and weaker directional tuning to wide-field moving stimuli. This approach reveals sub-lethal effects of imidacloprid in the visual motion detecting system of an important pollinator with likely implications for flight control, hovering and routing.

Photoreceptor signalling is sufficient to explain the detectability threshold of insect aerial pursuers

ABSTRACT An essential biological task for many flying insects is the detection of small, moving targets, such as when pursuing prey or conspecifics. Neural pathways underlying such ‘target-detecting’ behaviours have been investigated for their sensitivity and tuning properties (size, velocity). However, which stage of neuronal processing limits target detection is not yet known. Here, we investigated several skilled, aerial pursuers (males of four insect species), measuring the target-detection limit (signal-to-noise ratio) of light-adapted photoreceptors. We recorded intracellular responses to moving targets of varying size, extended well below the nominal resolution of single ommatidia. We found that the signal detection limit (2× photoreceptor noise) matches physiological or behavioural target-detection thresholds observed in each species. Thus, across a diverse range of flying insects, individual photoreceptor responses to changes in light intensity establish the sensitivity of the feature detection pathway, indicating later stages of processing are dedicated to feature tuning, tracking and selection. Summary: Across four insect species, the smallest target size a photoreceptor can robustly encode is sufficient to explain the detection limit of higher-order, target-detecting neurons or observed behavioural pursuits.