A `bright zone' in male hoverfly (Eristalis tenax) eyes and associated faster motion detection and increased contrast sensitivity

Temporal and spatial adaptation of transient responses to local features

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local “doublet” features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene.

Octopaminergic modulation of contrast sensitivity

Sensory systems adapt to prolonged stimulation by decreasing their response to continuous stimuli. Whereas visual motion adaptation has traditionally been studied in immobilized animals, recent work indicates that the animal's behavioral state influences the response properties of higher-order motion vision-sensitive neurons. During insect flight octopamine is released, and pharmacological octopaminergic activation can induce a fictive locomotor state. In the insect optic ganglia, lobula plate tangential cells (LPTCs) spatially pool input from local elementary motion detectors (EMDs) that correlate luminosity changes from two spatially discrete inputs after delaying the signal from one. The LPTC velocity optimum thereby depends on the spatial separation of the inputs and on the EMD's delay properties. Recently it was shown that behavioral activity increases the LPTC velocity optimum, with modeling suggesting this to originate in the EMD's temporal delay filters. However, behavior induces an additional post-EMD effect: the LPTC membrane conductance increases in flying flies. To physiologically investigate the degree to which activity causes presynaptic and postsynaptic effects, we conducted intracellular recordings of Eristalis horizontal system (HS) neurons. We constructed contrast response functions before and after adaptation at different temporal frequencies, with and without the octopamine receptor agonist chlordimeform (CDM). We extracted three motion adaptation components, where two are likely to be generated presynaptically of the LPTCs, and one within them. We found that CDM affected the early, EMD-associated contrast gain reduction, temporal frequency dependently. However, a CDM-induced change of the HS membrane conductance disappeared during and after visual stimulation. This suggests that physical activity mainly affects motion adaptation presynaptically of LPTCs, whereas post-EMD effects have a minimal effect.

Hyperacute motion detection by the lateral eyes of jumping spiders

Jumping spiders (Salticidae) are renowned for their high performing visual system. In addition to their prominent forward-facing telescope-like principal eyes, salticids possess two or three pairs of secondary eyes used for wide-angle motion detection. Salticids orient towards relevant sources of motion detected by the secondary eyes, enabling them to inspect the stimulus with their spatially acute principal eyes. The anteriormost pair of secondary eyes, the anterior lateral (AL) eyes, also faces forward and has higher spatial acuity than the other, laterally-facing, secondary eyes. We used small computer-generated targets to elicit orienting saccades from tethered jumping spiders in order to examine the perceptual limits of the AL eyes. We describe the contrast thresholds of male and female spiders, investigate the reaction time between stimulus appearance and initiation of orientation, as well as the minimum distance a stimulus must travel before eliciting a saccade. Our results show that female spiders react to lower contrast stimuli than males and demonstrate that the secondary eyes can detect stimulus displacements considerably smaller than the inter-receptor angle.

Rapid contrast gain reduction following motion adaptation

Neural and sensory systems adapt to prolonged stimulation to allow signaling across broader input ranges than otherwise possible with the limited bandwidth of single neurons and receptors. In the visual system, adaptation takes place at every stage of processing, from the photoreceptors that adapt to prevailing luminance conditions, to higher-order motion-sensitive neurons that adapt to prolonged exposure to motion. Recent experiments using dynamic, fluctuating visual stimuli indicate that adaptation operates on a time scale similar to that of the response itself. Further work from our own laboratory has highlighted the role for rapid motion adaptation in reliable encoding of natural image motion. Physiologically, motion adaptation can be broken down into four separate components. It is not clear from the previous studies which of these motion adaptation components are involved in the fast and dynamic response changes. To investigate the adapted response in more detail, we therefore analyzed the effect of motion adaptation using a test-adapt-test protocol with adapting durations ranging from 20 ms to 20 s. Our results underscore the very rapid rate of motion adaptation, suggesting that under free flight, visual motion-sensitive neurons continuously adapt to the changing scenery. This might help explain recent observations of strong invariance in the response to natural scenes with highly variable contrast and image structure.

A simple route to fabricate artificial compound eye structures

A biologically inspired compound-eye structure, which composes of ~5,867 honeycomb-patterned microlenses, was fabricated on a hemispherical shell. The fabrication process was simple and low-cost, which involves a femtosecond laser-enhanced wet etching and casting process followed by a thermomechanical process to convert the film into a hemispherical surface. By optimizing the parameters of thermomechanical process to form the curvilinear surface, the experimental result shows that the microlenses are omnidirectionally aligned on the dome with lens diameters of ~85 µm and the angle between two lens of ~2°, and the individual microlenses have rudimentary focusing and imaging properties. The artificial compound-eye structure fabricated by this method has great potential applications in scale-invariant processing, robot vision, and fast motion detection.

Temporal patterns of genetic and phenotypic variation in the epidemiologically important drone fly, Eristalis tenax

Eristalis tenax L. (Diptera: Syrphidae) is commonly known as the drone fly (adult) or rat-tailed maggot (immature). Both adults and immature stages are identified as potential mechanical vectors of mycobacterial pathogens, and early-stage maggots cause accidental myiasis. We compared four samples from Mount Fruška Gora, Serbia, with the aim of obtaining insights into the temporal variations and sexual dimorphism in the species. This integrative approach was based on allozyme loci, morphometric wing parameters (shape and size) and abdominal colour patterns. Consistent sexual dimorphism was observed, indicating that male specimens had lighter abdomens and smaller and narrower wings than females. The distribution of genetic diversity at polymorphic loci indicated genetic divergence among collection dates. Landmark-based geometric morphometrics revealed, contrary to the lack of divergence in wing size, significant wing shape variation throughout the year. In addition, temporal changes in the frequencies of the abdominal patterns observed are likely to relate to the biology of the species and ecological factors in the locality. Hence, the present study expands our knowledge of the genetic diversity and phenotypic plasticity of E. tenax. The quantification of such variability represents a step towards the evaluation of the adaptive potential of this species of medical and epidemiological importance.

Compound eyes and retinal information processing in miniature dipteran species match their specific ecological demands

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.

Spatial facilitation by a high-performance dragonfly target-detecting neuron

Many animals visualize and track small moving targets at long distances—be they prey, approaching predators or conspecifics. Insects are an excellent model system for investigating the neural mechanisms that have evolved for this challenging task. Specialized small target motion detector (STMD) neurons in the optic lobes of the insect brain respond strongly even when the target size is below the resolution limit of the eye. Many STMDs also respond robustly to small targets against complex stationary or moving backgrounds. We hypothesized that this requires a complex mechanism to avoid breakthrough responses by background features, and yet to adequately amplify the weak signal of tiny targets. We compared responses of dragonfly STMD neurons to small targets that begin moving within the receptive field with responses to targets that approach the same location along longer trajectories. We find that responses along longer trajectories are strongly facilitated by a mechanism that builds up slowly over several hundred milliseconds. This allows the neurons to give sustained responses to continuous target motion, thus providing a possible explanation for their extraordinary sensitivity.

Motion adaptation and the velocity coding of natural scenes

Estimating relative velocity in the natural environment is challenging because natural scenes vary greatly in contrast and spatial structure. Widely accepted correlation-based models for elementary motion detectors (EMDs) are sensitive to contrast and spatial structure and consequently generate ambiguous estimates of velocity. Identified neurons in the third optic lobe of the hoverfly can reliably encode the velocity of natural images largely independent of contrast, despite receiving inputs directly from arrays of such EMDs. This contrast invariance suggests an important role for additional neural processes in robust encoding of image motion. However, it remains unclear which neural processes are contributing to contrast invariance. By recording from horizontal system neurons in the hoverfly lobula, we show two activity-dependent adaptation mechanisms acting as near-ideal normalizers for images of different contrasts that would otherwise produce highly variable response magnitudes. Responses to images that are initially weak neural drivers are boosted over several hundred milliseconds. Responses to images that are initially strong neural drivers are reduced over longer time scales. These adaptation mechanisms appear to be matched to higher-order natural image statistics reconciling the neurons' accurate encoding of image velocity with the inherent ambiguity of correlation-based motion detectors.

Robust models for optic flow coding in natural scenes inspired by insect biology

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors.

Visual processing in the central bee brain

Visual scenes comprise enormous amounts of information from which nervous systems extract behaviorally relevant cues. In most model systems, little is known about the transformation of visual information as it occurs along visual pathways. We examined how visual information is transformed physiologically as it is communicated from the eye to higher-order brain centers using bumblebees, which are known for their visual capabilities. We recorded intracellularly in vivo from 30 neurons in the central bumblebee brain (the lateral protocerebrum) and compared these neurons to 132 neurons from more distal areas along the visual pathway, namely the medulla and the lobula. In these three brain regions (medulla, lobula, and central brain), we examined correlations between the neurons' branching patterns and their responses primarily to color, but also to motion stimuli. Visual neurons projecting to the anterior central brain were generally color sensitive, while neurons projecting to the posterior central brain were predominantly motion sensitive. The temporal response properties differed significantly between these areas, with an increase in spike time precision across trials and a decrease in average reliable spiking as visual information processing progressed from the periphery to the central brain. These data suggest that neurons along the visual pathway to the central brain not only are segregated with regard to the physical features of the stimuli (e.g., color and motion), but also differ in the way they encode stimuli, possibly to allow for efficient parallel processing to occur.

Visual control of flight speed in Drosophila melanogaster

Flight control in insects depends on self-induced image motion (optic flow), which the visual system must process to generate appropriate corrective steering maneuvers. Classic experiments in tethered insects applied rigorous system identification techniques for the analysis of turning reactions in the presence of rotating pattern stimuli delivered in open-loop. However, the functional relevance of these measurements for visual free-flight control remains equivocal due to the largely unknown effects of the highly constrained experimental conditions. To perform a systems analysis of the visual flight speed response under free-flight conditions, we implemented a 'one-parameter open-loop' paradigm using 'TrackFly' in a wind tunnel equipped with real-time tracking and virtual reality display technology. Upwind flying flies were stimulated with sine gratings of varying temporal and spatial frequencies, and the resulting speed responses were measured from the resulting flight speed reactions. To control flight speed, the visual system of the fruit fly extracts linear pattern velocity robustly over a broad range of spatio-temporal frequencies. The speed signal is used for a proportional control of flight speed within locomotor limits. The extraction of pattern velocity over a broad spatio-temporal frequency range may require more sophisticated motion processing mechanisms than those identified in flies so far. In Drosophila, the neuromotor pathways underlying flight speed control may be suitably explored by applying advanced genetic techniques, for which our data can serve as a baseline. Finally, the high-level control principles identified in the fly can be meaningfully transferred into a robotic context, such as for the robust and efficient control of autonomous flying micro air vehicles.

Feature detection and the hypercomplex property in insects

Discerning a target amongst visual 'clutter' is a complicated task that has been elegantly solved by flying insects, as evidenced by their mid-air interactions with conspecifics and prey. The neurophysiology of small-target motion detectors (STMDs) underlying these complex behaviors has recently been described and suggests that insects use mechanisms similar to those of hypercomplex cells of the mammalian visual cortex to achieve target-specific tuning. Cortical hypercomplex cells are end-stopped, which means that they respond optimally to small moving targets, with responses to extended bars attenuated. We review not only the underlying mechanisms involved in this tuning but also how recently proposed models provide a possible explanation for another remarkable property of these neurons - their ability to respond robustly to the motion of targets even against moving backgrounds.

The effects of individual differences and task difficulty on inattentional blindness

Most studies of inattentional blindness-the failure to notice an unexpected object when attention is focused elsewhere-have focused on one critical trial. For that trial, noticing the unexpected object might be a result of random variability, so that any given individual would be equally likely to notice the unexpected object. On the other hand, individual differences in the ability to perform the primary task might make noticing more likely for some individuals than for others. Increasing the difficulty of the primary task has been shown to decrease noticing rates for both brief static displays (Cartwright-Finch & Lavie, 2007) and dynamic monitoring tasks (Simons & Chabris, 1999). However, those studies did not explore whether individual differences in noticing arise from differences in the ability to perform the primary task. For our Experiment 1, we used a staircase procedure to equate primary task performance across individuals in a dynamic inattentional blindness task and found that the demands of the primary task affected noticing rates when individual differences in accuracy were minimized. In Experiment 2, we found that individual differences in primary task performance did not predict noticing of an unexpected object. Together, these findings suggest that although the demands of the primary task do affect inattentional blindness rates, individual differences in the ability to meet those demands do not.

The motion after-effect: local and global contributions to contrast sensitivity

Motion adaptation is a widespread phenomenon analogous to peripheral sensory adaptation, presumed to play a role in matching responses to prevailing current stimulus parameters and thus to maximize efficiency of motion coding. While several components of motion adaptation (contrast gain reduction, output range reduction and motion after-effect) have been described, previous work is inconclusive as to whether these are separable phenomena and whether they are locally generated. We used intracellular recordings from single horizontal system neurons in the fly to test the effect of local adaptation on the full contrast-response function for stimuli at an unadapted location. We show that contrast gain and output range reductions are primarily local phenomena and are probably associated with spatially distinct synaptic changes, while the antagonistic after-potential operates globally by transferring to previously unadapted locations. Using noise analysis and signal processing techniques to remove 'spikelets', we also characterize a previously undescribed alternating current component of adaptation that can explain several phenomena observed in earlier studies.

Color processing in the medulla of the bumblebee (Apidae: Bombus impatiens)

The mechanisms of processing a visual scene involve segregating features (such as color) into separate information channels at different stages within the brain, processing these features, and then integrating this information at higher levels in the brain. To examine how this process takes place in the insect brain, we focused on the medulla, an area within the optic lobe through which all of the visual information from the retina must pass before it proceeds to central brain areas. We used histological and immunocytochemical techniques to examine the bumblebee medulla and found that the medulla is divided into eight layers. We then recorded and morphologically identified 27 neurons with processes in the medulla. During our recordings we presented color cues to determine whether response types correlated with locations of the neural branching patterns of the filled neurons among the medulla layers. Neurons in the outer medulla layers had less complex color responses compared to neurons in the inner medulla layers and there were differences in the temporal dynamics of the responses among the layers. Progressing from the outer to the inner medulla, neurons in the different layers appear to process increasingly complex aspects of the natural visual scene.

Visual ecology of Indian carpenter bees II: adaptations of eyes and ocelli to nocturnal and diurnal lifestyles

Most bees are diurnal, with behaviour that is largely visually mediated, but several groups have made evolutionary shifts to nocturnality, despite having apposition compound eyes unsuited to vision in dim light. We compared the anatomy and optics of the apposition eyes and the ocelli of the nocturnal carpenter bee, Xylocopa tranquebarica, with two sympatric species, the strictly diurnal X. leucothorax and the occasionally crepuscular X. tenuiscapa. The ocelli of the nocturnal X. tranquebarica are unusually large (diameter ca. 1 mm) and poorly focussed. Moreover, their apposition eyes show specific visual adaptations for vision in dim light, including large size, large facets and very wide rhabdoms, which together make these eyes 9 times more sensitive than those of X. tenuiscapa and 27 times more sensitive than those of X. leucothorax. These differences in optical sensitivity are surprisingly small considering that X. tranquebarica can fly on moonless nights when background luminance is as low as 10(-5) cd m(-2), implying that this bee must employ additional visual strategies to forage and find its way back to the nest. These strategies may include photoreceptors with longer integration times and higher contrast gains as well as higher neural summation mechanisms for increasing visual reliability in dim light.

Dynamic photorefraction system: an offline application for the dynamic analysis of ocular focus and pupil size from photorefraction images

Eccentric photorefraction is an optical technique used to assess static and/or dynamic changes in ocular focus (accommodation), ocular alignment (vergence) and pupil size. In this paper, we have developed and tested an offline application namely the dynamic photorefraction system (DPRS) which allows an accurate analysis of accommodation and pupil size from eccentric photorefraction images. The application uses the Microsoft componentized technology known as the Component Object Model (COM), includes distinct libraries for importing photorefraction videos and provides an accurate analysis and output of pupil size and accommodation. In addition, the system can interface with any custom built photorefractor allowing a widespread application in vision science experiments involving simultaneous measures of ocular focus and pupil size.

Vision egg: an open-source library for realtime visual stimulus generation

Modern computer hardware makes it possible to produce visual stimuli in ways not previously possible. Arbitrary scenes, from traditional sinusoidal gratings to naturalistic 3D scenes can now be specified on a frame-by-frame basis in realtime. A programming library called the Vision Egg that aims to make it easy to take advantage of these innovations. The Vision Egg is a free, open-source library making use of OpenGL and written in the high-level language Python with extensions in C. Careful attention has been paid to the issues of luminance and temporal calibration, and several interfacing techniques to input devices such as mice, movement tracking systems, and digital triggers are discussed. Together, these make the Vision Egg suitable for many psychophysical, electrophysiological, and behavioral experiments. This software is available for free download at visionegg.org.

Higher order visual input to the mushroom bodies in the bee, Bombus impatiens

To produce appropriate behaviors based on biologically relevant associations, sensory pathways conveying different modalities are integrated by higher-order central brain structures, such as insect mushroom bodies. To address this function of sensory integration, we characterized the structure and response of optic lobe (OL) neurons projecting to the calyces of the mushroom bodies in bees. Bees are well known for their visual learning and memory capabilities and their brains possess major direct visual input from the optic lobes to the mushroom bodies. To functionally characterize these visual inputs to the mushroom bodies, we recorded intracellularly from neurons in bumblebees (Apidae: Bombus impatiens) and a single neuron in a honeybee (Apidae: Apis mellifera) while presenting color and motion stimuli. All of the mushroom body input neurons were color sensitive while a subset was motion sensitive. Additionally, most of the mushroom body input neurons would respond to the first, but not to subsequent, presentations of repeated stimuli. In general, the medulla or lobula neurons projecting to the calyx signaled specific chromatic, temporal, and motion features of the visual world to the mushroom bodies, which included sensory information required for the biologically relevant associations bees form during foraging tasks.

Manganese-enhanced MRI of layer-specific activity in the visual cortex from awake and free-moving rats

Cortical responses to visual stimulation have been studied extensively in the rodent, but often require post-stimulation ex vivo examination of the tissue. Here, we test the hypothesis that visual stimulus-dependent cortical activity from awake and free-moving rats can be encoded following systemically administered MnCl(2), and activity subsequently readout using manganese-enhanced MRI (MEMRI), a technique that can be performed without sacrificing the animal. Unanesthetized Sprague-Dawley rats, with or without systemic injection of MnCl(2), were maintained for 8 h in either a visually stimulating environment or darkness. To identify vision-dependent changes in cortical activity, animals were anesthetized and cortices were examined by 3D RARE MEMRI. Mean signal intensities in sub-cortical regions (e.g., superior colliculus and the lateral geniculate), and cortical regions (primary and accessory visual cortices) were compared. Cortex linearization was performed to aid in layer-specific signal intensity comparisons. Manganese administration alone globally increased signal intensity in the brain (P<0.0001). In visually stimulated and unstimulated rats, layer-specific analysis revealed that stimulated rats had on average significantly (P<0.05) higher signal intensities in layers IV and V of the primary visual cortex, as well as in deeper portions of the superficial superior colliculus, relative to dark adapted rats. Such differences went undetected without layer-specific analysis. We demonstrate, for the first time, the feasibility of layer-specific stimulus-dependant non-invasive MEMRI readout after encoding activity in awake and free moving rats. Future MEMRI studies are envisioned that measure the effects on cortical activity of sensory stimulation, as well as normal development, disease, plasticity, and therapy in longitudinal studies.

A model for the detection of moving targets in visual clutter inspired by insect physiology

We present a computational model for target discrimination based on intracellular recordings from neurons in the fly visual system. Determining how insects detect and track small moving features, often against cluttered moving backgrounds, is an intriguing challenge, both from a physiological and a computational perspective. Previous research has characterized higher-order neurons within the fly brain, known as ‘small target motion detectors’ (STMD), that respond robustly to moving features, even when the velocity of the target is matched to the background (i.e. with no relative motion cues). We recorded from intermediate-order neurons in the fly visual system that are well suited as a component along the target detection pathway. This full-wave rectifying, transient cell (RTC) reveals independent adaptation to luminance changes of opposite signs (suggesting separate ON and OFF channels) and fast adaptive temporal mechanisms, similar to other cell types previously described. From this physiological data we have created a numerical model for target discrimination. This model includes nonlinear filtering based on the fly optics, the photoreceptors, the 1^st order interneurons (Large Monopolar Cells), and the newly derived parameters for the RTC. We show that our RTC-based target detection model is well matched to properties described for the STMDs, such as contrast sensitivity, height tuning and velocity tuning. The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear ‘matched filter’ to successfully detect most targets from the background. Importantly, this model can explain this type of feature discrimination without the need for relative motion cues.

The processing of color, motion, and stimulus timing are anatomically segregated in the bumblebee brain

Animals use vision to perform such diverse behaviors as finding food, interacting socially with other animals, choosing a mate, and avoiding predators. These behaviors are complex and the visual system must process color, motion, and pattern cues efficiently so that animals can respond to relevant stimuli. The visual system achieves this by dividing visual information into separate pathways, but to what extent are these parallel streams separated in the brain? To answer this question, we recorded intracellularly in vivo from 105 morphologically identified neurons in the lobula, a major visual processing structure of bumblebees (Bombus impatiens). We found that these cells have anatomically segregated dendritic inputs confined to one or two of six lobula layers. Lobula neurons exhibit physiological characteristics common to their respective input layer. Cells with arborizations in layers 1-4 are generally indifferent to color but sensitive to motion, whereas layer 5-6 neurons often respond to both color and motion cues. Furthermore, the temporal characteristics of these responses differ systematically with dendritic branching pattern. Some layers are more temporally precise, whereas others are less precise but more reliable across trials. Because different layers send projections to different regions of the central brain, we hypothesize that the anatomical layers of the lobula are the structural basis for the segregation of visual information into color, motion, and stimulus timing.

Retinotopic organization of small-field-target-detecting neurons in the insect visual system

BACKGROUND

Despite having tiny brains and relatively low-resolution compound eyes, many fly species frequently engage in precisely controlled aerobatic pursuits of conspecifics. Recent investigations into high-order processing in the fly visual system have revealed a class of neurons, coined small-target-motion detectors (STMDs), capable of responding robustly to target motion against the motion of background clutter. Despite limited spatial acuity in the insect eye, these neurons display exquisite sensitivity to small targets.

RESULTS

We recorded intracellularly from morphologically identified columnar neurons in the lobula complex of the hoverfly Eristalis tenax. We show that these columnar neurons with exquisitely small receptive fields, like their large-field counterparts recently described from both male and female flies, have an extreme selectivity for the motion of small targets. In doing so, we provide the first physiological characterization of small-field neurons in female flies. These retinotopically organized columnar neurons include both direction-selective and nondirection-selective classes covering a large area of visual space.

CONCLUSIONS

The retinotopic arrangement of lobula columnar neurons sensitive to the motion of small targets makes a strong case for these neurons as important precursors in the local processing of target motion. Furthermore, the continued response of STMDs with such small receptive fields to the motion of small targets in the presence of moving background clutter places further constraints on the potential mechanisms underlying their small-target tuning.

EMG spike time difference based feedback control

Flight control in insects has been studied extensively; however the underlying neural mechanisms are not fully understood. Output from the central nervous system (CNS) must drive wing phase shifts and flight muscle depressor asymmetries associated with adaptive flight maneuvers. These maneuvers will, in turn, influence the insect's sensory environment, thus closing the feedback loop. We present a novel method that utilizes asymmetrical timing of bilateral depressor muscles, the forewing first basalars (m97), of the locust to close a visual feedback loop in a computer-generated flight simulator. The method converts the time difference between left and right m97s to analog voltage values. These voltage values can be obtained using open-loop experiments (visual motion controlled by the experimenter), or can be used to control closed-loop experiments (muscle activity controls the visual stimuli) experiments. Electromyographic (EMG) signals were obtained from right and left m97 muscles; spike time difference between them was calculated and converted to voltage values. Testing this circuit with real animals, we were able to detect the spike time difference and convert that to voltage that controlled the presentation of a stimulus in a closed-loop environment. This method may be used in conjunction with the flight simulator to understand the manner in which sensory information is integrated with the activity of the flight circuitry to study the neural control of this complex behaviour.