Visual system of calliphorid flies: motion- and orientation-sensitive visual interneurons supplying dorsal optic glomeruli

Bioinspired figure-ground discrimination via visual motion smoothing

Flies detect and track moving targets among visual clutter, and this process mainly relies on visual motion. Visual motion is analyzed or computed with the pathway from the retina to T4/T5 cells. The computation of local directional motion was formulated as an elementary movement detector (EMD) model more than half a century ago. Solving target detection or figure-ground discrimination problems can be equivalent to extracting boundaries between a target and the background based on the motion discontinuities in the output of a retinotopic array of EMDs. Individual EMDs cannot measure true velocities, however, due to their sensitivity to pattern properties such as luminance contrast and spatial frequency content. It remains unclear how local directional motion signals are further integrated to enable figure-ground discrimination. Here, we present a computational model inspired by fly motion vision. Simulations suggest that the heavily fluctuating output of an EMD array is naturally surmounted by a lobula network, which is hypothesized to be downstream of the local motion detectors and have parallel pathways with distinct directional selectivity. The lobula network carries out a spatiotemporal smoothing operation for visual motion, especially across time, enabling the segmentation of moving figures from the background. The model qualitatively reproduces experimental observations in the visually evoked response characteristics of one type of lobula columnar (LC) cell. The model is further shown to be robust to natural scene variability. Our results suggest that the lobula is involved in local motion-based target detection.

Parallel motion vision pathways in the brain of a tropical bee

Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brain's navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bee's current position in space in relation to its nest, i.e., perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.

Neural organization of the third optic neuropil, the lobula, in the highly visual semiterrestrial crab Neohelice granulata

The visual neuropils (lamina, medulla and lobula complex), of malacostracan crustaceans and hexapods have many organizational principles, cell types and functional properties in common. Information about the cellular elements that compose the crustacean lobula is scarce especially when focusing on small columnar cells. Semiterrestrial crabs possess a highly developed visual system and display conspicuous visually guided behaviors. In particular, Neohelice granulata has been previously used to describe the cellular components of the first two optic neuropils using Golgi impregnation technique. Here, we present a comprehensive description of individual elements composing the third optic neuropil, the lobula, of that same species. We characterized a wide variety of elements (140 types) including input terminals and lobula columnar, centrifugal and input columnar elements. Results reveal a very dense and complex neuropil. We found a frequently impregnated input element (suggesting a supernumerary cartridge representation) that arborizes in the third layer of the lobula and that presents four variants each with ramifications organized following one of the four cardinal axes suggesting a role in directional processing. We also describe input elements with two neurites branching in the third layer, probably connecting with the medulla and lobula plate. These facts suggest that this layer is involved in the directional motion detection pathway in crabs. We analyze and discuss our findings considering the similarities and differences found between the layered organization and components of this crustacean lobula and the lobula of insects. This article is protected by copyright. All rights reserved.

Convergent evolution of optic lobe neuropil in Pancrustacea

A prevailing opinion since 1926 has been that optic lobe organization in malacostracan crustaceans and insects reflects a corresponding organization in their common ancestor. Support for this refers to malacostracans and insects both possessing three, in some instances four, nested retinotopic neuropils beneath their compound eyes. Historically, the rationale for claiming homology of malacostracan and insect optic lobes referred to those commonalities, and to comparable arrangements of neurons. However, recent molecular phylogenetics has firmly established that Malacostraca belong to Multicrustacea, whereas Hexapoda and its related taxa Cephalocarida, Branchiopoda, and Remipedia belong to the phyletically distinct clade Allotriocarida. Insects are more closely related to remipedes than are either to malacostracans. Reconciling neuroanatomy with molecular phylogenies has been complicated by studies showing that the midbrains of remipedes share many attributes with the midbrains of malacostracans. Here we review the organization of the optic lobes in Malacostraca and Insecta to inquire which of their characters correspond genealogically across Pancrustacea and which characters do not. We demonstrate that neuroanatomical characters pertaining to the third optic lobe neuropil, called the lobula complex, may indicate convergent evolution. Distinctions of the malacostracan and insect lobula complexes are sufficient to align neuroanatomical descriptions of the pancrustacean optic lobes within the constraints of molecular-based phylogenies.

Shore crabs reveal novel evolutionary attributes of the mushroom body

Neural organization of mushroom bodies is largely consistent across insects, whereas the ancestral ground pattern diverges broadly across crustacean lineages resulting in successive loss of columns and the acquisition of domed centers retaining ancestral Hebbian-like networks and aminergic connections. We demonstrate here a major departure from this evolutionary trend in Brachyura, the most recent malacostracan lineage. In the shore crab Hemigrapsus nudus, instead of occupying the rostral surface of the lateral protocerebrum, mushroom body calyces are buried deep within it with their columns extending outwards to an expansive system of gyri on the brain’s surface. The organization amongst mushroom body neurons reaches extreme elaboration throughout its constituent neuropils. The calyces, columns, and especially the gyri show DC0 immunoreactivity, an indicator of extensive circuits involved in learning and memory.

Representation of the stomatopod's retinal midband in the optic lobes: Putative neural substrates for integrating chromatic, achromatic and polarization information

Stomatopods have an elaborate visual system served by a retina that is unique to this class of pancrustaceans. Its upper and lower eye hemispheres encode luminance and linear polarization while an equatorial band of photoreceptors termed the midband detects color, circularly polarized light and linear polarization in the ultraviolet. In common with many malacostracan crustaceans, stomatopods have stalked eyes, but they can move these independently within three degrees of rotational freedom. Both eyes separately use saccadic and scanning movements but they can also move in a coordinated fashion to track selected targets or maintain a forward eyestalk posture during swimming. Visual information is initially processed in the first two optic neuropils, the lamina and the medulla, where the eye's midband is represented by enlarged regions within each neuropil that contain populations of neurons, the axons of which are segregated from the neuropil regions subtending the hemispheres. Neuronal channels representing the midband extend from the medulla to the lobula where populations of putative inhibitory glutamic acid decarboxylase-positive neurons and tyrosine hydroxylase-positive neurons intrinsic to the lobula have specific associations with the midband. Here we investigate the organization of the midband representation in the medulla and the lobula in the context of their overall architecture. We discuss the implications of observed arrangements, in which midband inputs to the lobula send out collaterals that extend across the retinotopic mosaic pertaining to the hemispheres. This organization suggests an integrative design that diverges from the eumalacostracan ground pattern and, for the stomatopod, enables color and polarization information to be integrated with luminance information that presumably encodes shape and motion.

A predictive focus of gain modulation encodes target trajectories in insect vision

When a human catches a ball, they estimate future target location based on the current trajectory. How animals, small and large, encode such predictive processes at the single neuron level is unknown. Here we describe small target-selective neurons in predatory dragonflies that exhibit localized enhanced sensitivity for targets displaced to new locations just ahead of the prior path, with suppression elsewhere in the surround. This focused region of gain modulation is driven by predictive mechanisms, with the direction tuning shifting selectively to match the target’s prior path. It involves a large local increase in contrast gain which spreads forward after a delay (e.g. an occlusion) and can even transfer between brain hemispheres, predicting trajectories moved towards the visual midline from the other eye. The tractable nature of dragonflies for physiological experiments makes this a useful model for studying the neuronal mechanisms underlying the brain’s remarkable ability to anticipate moving stimuli.

DOI:http://dx.doi.org/10.7554/eLife.26478.001

Catching a ball requires a person to track the speed and direction of a small moving target often against a cluttered and varying background. Predatory insects, like dragonflies, face a similar challenge when they pursue their prey through the air. The task is made a little easier, however, by the fact that most moving targets tend to follow predictable trajectories. Indeed, animals are also better at tracking targets that follow smooth continuous trajectories, suggesting that brains have evolved to exploit the normal behavior of visual stimuli to reduce their workload

To find out how this process works, Wiederman, Fabian et al. studied the brains of dragonflies as they watched a black square intended to mimic prey. Brain cells called Small Target Motion Detectors (or STMD neurons for short) became more active in response to the target. But rather than simply following the target, the STMD neurons instead predicted its future location. In fact, individual neurons were more sensitive to movements occurring just ahead of the target’s current position, and less sensitive to movements occurring elsewhere.

If the target abruptly disappeared, the point in space where the neurons were most sensitive to movement continued to gradually move forward over time. Given that real-life targets typically disappear when they move behind other objects, this suggests that the brain is predicting where the target is most likely to reappear. The STMD neurons became more sensitive to movement by increasing their ability to detect differences in brightness between the target and its background. In some cases, the neurons increased their sensitivity more than five-fold.

Insects and mammals last shared a common ancestor more than 500 million years ago, and, in many respects, mammalian brains are substantially more complex than insect brains. Nevertheless, the results of Wiederman, Fabian et al. show that the insect brain can perform visual tasks that were previously associated only with mammals. Neuroscientists and engineers have used the insect brain for decades to study the circuits that support biological processes. In the coming years, insects such as the dragonfly may enable us to explore how visual regions of the brain predict future events. This knowledge could ultimately be applied to artificial vision systems, such as those in self-driving cars.

DOI:http://dx.doi.org/10.7554/eLife.26478.002

An insect-inspired model for visual binding I: learning objects and their characteristics

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

An insect-inspired model for visual binding II: functional analysis and visual attention

We have developed a neural network model capable of performing visual binding inspired by neuronal circuitry in the optic glomeruli of flies: a brain area that lies just downstream of the optic lobes where early visual processing is performed. This visual binding model is able to detect objects in dynamic image sequences and bind together their respective characteristic visual features-such as color, motion, and orientation-by taking advantage of their common temporal fluctuations. Visual binding is represented in the form of an inhibitory weight matrix which learns over time which features originate from a given visual object. In the present work, we show that information represented implicitly in this weight matrix can be used to explicitly count the number of objects present in the visual image, to enumerate their specific visual characteristics, and even to create an enhanced image in which one particular object is emphasized over others, thus implementing a simple form of visual attention. Further, we present a detailed analysis which reveals the function and theoretical limitations of the visual binding network and in this context describe a novel network learning rule which is optimized for visual binding.

Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees

The ability to generalize over naturally occurring variation in cues indicating food or predation risk is highly useful for efficient decision-making in many animals. Honeybees have remarkable visual cognitive abilities, allowing them to classify visual patterns by common features despite having a relatively miniature brain. Here we ask the question whether generalization requires complex visual recognition or whether it can also be achieved with relatively simple neuronal mechanisms. We produced several simple models inspired by the known anatomical structures and neuronal responses within the bee brain and subsequently compared their ability to generalize achromatic patterns to the observed behavioural performance of honeybees on these cues. Neural networks with just eight large-field orientation-sensitive input neurons from the optic ganglia and a single layer of simple neuronal connectivity within the mushroom bodies (learning centres) show performances remarkably similar to a large proportion of the empirical results without requiring any form of learning, or fine-tuning of neuronal parameters to replicate these results. Indeed, a model simply combining sensory input from both eyes onto single mushroom body neurons returned correct discriminations even with partial occlusion of the patterns and an impressive invariance to the location of the test patterns on the eyes. This model also replicated surprising failures of bees to discriminate certain seemingly highly different patterns, providing novel and useful insights into the inner workings facilitating and limiting the utilisation of visual cues in honeybees. Our results reveal that reliable generalization of visual information can be achieved through simple neuronal circuitry that is biologically plausible and can easily be accommodated in a tiny insect brain.

We present two very simple neural network models based directly on the neural circuitry of honeybees. These models, using just four large-field visual input neurons from each eye that sparsely connect to a single layer of interneurons within the bee brain learning centres, are able to discriminate complex achromatic patterns without the need for an internal image representation. One model combining the visual input from both eyes showed an impressive invariance to the location of the test patterns on the retina and even succeeded with the partial occlusion of these cues, which would obviously be advantageous for free-flying bees. We show that during generalization experiments, where the models have to distinguish between two novel stimuli, one more similar to a training set of patterns, that both simple models have performances very similar to the empirical honeybee results. Our models only failed to generalize to the correct test pattern when the distractor pattern contained only a few small differences; we discuss how the protocols employed during training enable honeybees to still distinguish these stimuli. This research provides new insights into the surprisingly limited neurobiological complexity that is required for specific cognitive abilities, and how these mechanisms may be employed within the tiny brain of the bee.

Automatic Segmentation of Drosophila Neural Compartments Using GAL4 Expression Data Reveals Novel Visual Pathways

Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates.

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Genome-scale enhancer expression patterns can be used to predict brain structure

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Automated clustering of images finds known structures such as olfactory glomeruli

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Results identify GAL4 lines with strong expression in the predicted structures

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We validate novel predictions to reveal previously undescribed optic glomeruli

Arthropod eyes: The early Cambrian fossil record and divergent evolution of visual systems

Four types of eyes serve the visual neuropils of extant arthropods: compound retinas composed of adjacent facets; a visual surface populated by spaced eyelets; a smooth transparent cuticle providing inwardly directed lens cylinders; and single-lens eyes. The first type is a characteristic of pancrustaceans, the eyes of which comprise lenses arranged as hexagonal or rectilinear arrays, each lens crowning 8-9 photoreceptor neurons. Except for Scutigeromorpha, the second type typifies Myriapoda whose relatively large eyelets surmount numerous photoreceptive rhabdoms stacked together as tiers. Scutigeromorph eyes are facetted, each lens crowning some dozen photoreceptor neurons of a modified apposition-type eye. Extant chelicerate eyes are single-lensed except in xiphosurans, whose lateral eyes comprise a cuticle with a smooth outer surface and an inner one providing regular arrays of lens cylinders. This account discusses whether these disparate eye types speak for or against divergence from one ancestral eye type. Previous considerations of eye evolution, focusing on the eyes of trilobites and on facet proliferation in xiphosurans and myriapods, have proposed that the mode of development of eyes in those taxa is distinct from that of pancrustaceans and is the plesiomorphic condition from which facetted eyes have evolved. But the recent discovery of enormous regularly facetted compound eyes belonging to early Cambrian radiodontans suggests that high-resolution facetted eyes with superior optics may be the ground pattern organization for arthropods, predating the evolution of arthrodization and jointed post-protocerebral appendages. Here we provide evidence that compound eye organization in stem-group euarthropods of the Cambrian can be understood in terms of eye morphologies diverging from this ancestral radiodontan-type ground pattern. We show that in certain Cambrian groups apposition eyes relate to fixed or mobile eyestalks, whereas other groups reveal concomitant evolution of sessile eyes equipped with optics typical of extant xiphosurans. Observations of fossil material, including that of trilobites and eurypterids, support the proposition that the ancestral compound eye was the apposition type. Cambrian arthropods include possible precursors of mandibulate eyes. The latter are the modified compound eyes, now sessile, and their underlying optic lobes exemplified by scutigeromorph chilopods, and the mobile stalked compound eyes and more elaborate optic lobes typifying Pancrustacea. Radical divergence from an ancestral apposition type is demonstrated by the evolution of chelicerate eyes, from doublet sessile-eyed stem-group taxa to special apposition eyes of xiphosurans, the compound eyes of eurypterids, and single-lens eyes of arachnids. Different eye types are discussed with respect to possible modes of life of the extinct species that possessed them, comparing these to extant counterparts and the types of visual centers the eyes might have served.

Temporal statistics of natural image sequences generated by movements with insect flight characteristics

Many flying insects, such as flies, wasps and bees, pursue a saccadic flight and gaze strategy. This behavioral strategy is thought to separate the translational and rotational components of self-motion and, thereby, to reduce the computational efforts to extract information about the environment from the retinal image flow. Because of the distinguishing dynamic features of this active flight and gaze strategy of insects, the present study analyzes systematically the spatiotemporal statistics of image sequences generated during saccades and intersaccadic intervals in cluttered natural environments. We show that, in general, rotational movements with saccade-like dynamics elicit fluctuations and overall changes in brightness, contrast and spatial frequency of up to two orders of magnitude larger than translational movements at velocities that are characteristic of insects. Distinct changes in image parameters during translations are only caused by nearby objects. Image analysis based on larger patches in the visual field reveals smaller fluctuations in brightness and spatial frequency composition compared to small patches. The temporal structure and extent of these changes in image parameters define the temporal constraints imposed on signal processing performed by the insect visual system under behavioral conditions in natural environments.

Chromatic processing in the anterior optic tubercle of the honey bee brain

Color vision in honey bees (Apis mellifera) has been extensively studied at the behavioral level and, to a lesser degree, at the physiological level by means of electrophysiological intracellular recordings of single neurons. Few visual neurons have been so far characterized in the lateral protocerebrum of bees. Therefore, the possible implication of this region in chromatic processing remains unknown. We performed in vivo calcium imaging of interneurons in the anterior optic tubercle (AOTu) of honey bees upon visual stimulation of the compound eye to analyze chromatic response properties. Stimulation with distinct monochromatic lights (ultraviolet [UV], blue, and green) matching the sensitivity of the three photoreceptor types of the bee retina induced different signal amplitudes, temporal dynamics, and spatial activity patterns in the AOTu intertubercle network, thus revealing intricate chromatic processing properties. Green light strongly activated both the dorsal and ventral lobes of the AOTu's major unit; blue light activated the dorsal lobe more while UV light activated the ventral lobe more. Eye stimulation with mixtures of blue and green light induced suppression phenomena in which responses to the mixture were lower than those to the color components, thus concurring with color-opponent processing. These data provide evidence for a spatial segregation of color processing in the AOTu, which may serve for navigation purposes.

Lobula-specific visual projection neurons are involved in perception of motion-defined second-order motion in Drosophila

A wide variety of animal species including humans and fruit flies see second-order motion although they lack coherent spatiotemporal correlations in luminance. Recent electrophysiological recordings, together with intensive psychophysical studies, are bringing to light the neural underpinnings of second-order motion perception in mammals. However, where and how the higher-order motion signals are processed in the fly brain is poorly understood. Using the rich genetic tools available in Drosophila and examining optomotor responses in fruit flies to several stimuli, we revealed that two lobula-specific visual projection neurons, specifically connecting the lobula and the central brain, are involved in the perception of motion-defined second-order motion, independent of whether the second-order feature is moving perpendicular or opposite to the local first-order motion. By contrast, blocking these neurons has no effect on first-order and flicker-defined second-order stimuli in terms of response delay. Our results suggest that visual neuropils deep in the optic lobe and the central brain, whose functional roles in motion processing were previously unclear, may be specifically required for motion-defined motion processing.

Neuronal representation of visual motion and orientation in the fly medulla

In insects, the first extraction of motion and direction clues from local brightness modulations is thought to take place in the medulla. However, whether and how these computations are represented in the medulla stills remain widely unknown, because electrical recording of the neurons in the medulla is difficult. As an effort to overcome this difficulty, we employed local electroporation in vivo in the medulla of the blowfly (Calliphora vicina) to stain small ensembles of neurons with a calcium-sensitive dye. We studied the responses of these neuronal ensembles to spatial and temporal brightness modulations and found selectivity for grating orientation. In contrast, the responses to the two opposite directions of motion of a grating with the same orientation were similar in magnitude, indicating that strong directional selectivity is either not present in the types of neurons covered by our data set, or that direction-selective signals are too closely spaced to be distinguished by our calcium imaging. The calcium responses also showed a bell-shaped dependency on the temporal frequency of drifting gratings, with an optimum higher than that observed in one of the subsequent processing stages, i.e., the lobula plate. Medulla responses were elicited by on- as well as off-stimuli with some spatial heterogeneity in the sensitivity for “on” and “off”, and in the polarity of the responses. Medulla neurons thus show similarities to some established principles of motion and edge detection in the vertebrate visual system.

The central complex of the flesh fly, Neobellieria bullata: recordings and morphologies of protocerebral inputs and small-field neurons

The central complex in the brains of insects is a series of midline neuropils involved in motor control, sensory integration, and associative learning. To understand better the role of this center and its supply of sensory information, intracellular recordings and dye fills were made of central complex neurons in the fly, Neobellieria bullata. Recordings were obtained from 24 neurons associated with the ellipsoid body, fan-shaped body, and protocerebral bridge, all of which receive both visual and mechanosensory information from protocerebral centers. One neuron with dendrites in an area of the lateral protocerebrum associated with motion-sensitive outputs from the optic lobes invades the entire protocerebral bridge and was driven by visual motion. Inputs to the fan-shaped body and ellipsoid body responded both to visual stimuli and to air puffs directed at the head and abdomen. Intrinsic neurons in both of these structures respond to changes in illumination. A putative output neuron connecting the protocerebral bridge, the fan-shaped body, and one of the lateral accessory lobes showed opponent responses to moving visual stimuli. These recordings identify neurons with response properties previously known only from extracellular recordings in other species. Dye injections into neurons connecting the central complex with areas of the protocerebrum suggest that some classes of inputs into the central complex are electrically coupled.

Optic glomeruli and their inputs in Drosophila share an organizational ground pattern with the antennal lobes

Studying the insect visual system provides important data on the basic neural mechanisms underlying visual processing. As in vertebrates, the first step in visual processing in insects is through a series of retinotopic neurons. Recent studies on flies have found that these converge onto assemblies of columnar neurons in the lobula, the axons of which segregate to project to discrete optic glomeruli in the lateral protocerebrum. This arrangement is much like the fly's olfactory system, in which afferents target uniquely identifiable olfactory glomeruli. Here, whole-cell patch recordings show that even though visual primitives are unreliably encoded by single lobula output neurons because of high synaptic noise, they are reliably encoded by the ensemble of outputs. At a glomerulus, local interneurons reliably code visual primitives, as do projection neurons conveying information centrally from the glomerulus. These observations demonstrate that in Drosophila, as in other dipterans, optic glomeruli are involved in further reconstructing the fly's visual world. Optic glomeruli and antennal lobe glomeruli share the same ancestral anatomical and functional ground pattern, enabling reliable responses to be extracted from converging sensory inputs.

Figure tracking by flies is supported by parallel visual streams

Visual figures may be distinguished based on elementary motion or higher-order non-Fourier features, and flies track both. The canonical elementary motion detector, a compact computation for Fourier motion direction and amplitude, can also encode higher-order signals provided elaborate preprocessing. However, the way in which a fly tracks a moving figure containing both elementary and higher-order signals has not been investigated. Using a novel white noise approach, we demonstrate that (1) the composite response to an object containing both elementary motion (EM) and uncorrelated higher-order figure motion (FM) reflects the linear superposition of each component; (2) the EM-driven component is velocity-dependent, whereas the FM component is driven by retinal position; (3) retinotopic variation in EM and FM responses are different from one another; (4) the FM subsystem superimposes saccadic turns upon smooth pursuit; and (5) the two systems in combination are necessary and sufficient to predict the full range of figure tracking behaviors, including those that generate no EM cues at all. This analysis requires an extension of the model that fly motion vision is based on simple elementary motion detectors and provides a novel method to characterize the subsystems responsible for the pursuit of visual figures.

Insect form vision as one potential shaping force of spider web decoration design

Properties of prey sensory systems are important factors shaping the design of signals generated by organisms exploiting them. In this study we assessed how prey sensory preference affected the exploiter signal design by investigating the evolutionary relationship and relative attractiveness of linear and cruciate form web decorations built by Argiope spiders. Because insects have an innate preference for bilaterally symmetrical patterns, we hypothesized that cruciate form decorations were evolved from linear form due to their higher visual attractiveness to insects. We first reconstructed a molecular phylogeny of the Asian members of the genus Argiope using mitochondrial markers to infer the evolutionary relationship of two decoration forms. Results of ancestral character state reconstruction showed that the linear form was ancestral and the cruciate form derived. To evaluate the luring effectiveness of two decoration forms, we performed field experiments in which the number and orientation of decoration bands were manipulated. Decoration bands arranged in a cruciate form were significantly more attractive to insects than those arranged in a linear form, no matter whether they were composed of silks or dummies. Moreover, dummy decoration bands arranged in a cruciate form attracted significantly more insects than those arranged in a vertical/horizontal form. Such results suggest that pollinator insects' innate preference for certain bilateral or radial symmetrical patterns might be one of the driving forces shaping the arrangement pattern of spider web decorations.

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.

Organization of local interneurons in optic glomeruli of the dipterous visual system and comparisons with the antennal lobes

The lateral protocerebrum of the fly's brain is composed of a system of optic glomeruli, the organization of which compares to that of antennal lobe glomeruli. Each optic glomerulus receives converging axon terminals from a unique ensemble of optic lobe output neurons. Glomeruli are interconnected by systems of spiking and nonspiking local interneurons that are morphologically similar to diffuse and polarized local interneurons in the antennal lobes. GABA-like immunoreactive processes richly supply optic glomeruli, which are also invaded by processes originating from the midbrain and subesophageal ganglia. These arrangements support the suggestion that circuits amongst optic glomeruli refine and elaborate visual information carried by optic lobe outputs, relaying data to long-axoned neurons that extend to other parts of the central nervous system including thoracic ganglia. The representation in optic glomeruli of other modalities suggests that gating of visual information by other sensory inputs, a phenomenon documented from the recordings of descending neurons, could occur before the descending neuron dendrites. The present results demonstrate that future studies must consider the roles of other senses in visual processing.

Visual system of calliphorid flies: organization of optic glomeruli and their lobula complex efferents

Reconstructions of silver-stained brains revealed 27 optic glomeruli that occupy a major volume of the lateral protocerebrum. Axons from different morphological types of columnar output neurons from the lobula complex sort out to specific glomeruli. Glomeruli are partially enwrapped by glial processes and are invaded by the dendrites and terminals of local interneurons that connect different glomeruli in a manner analogous to local interneurons in the antennal lobes. Each type of columnar neuron contributes to a palisade-like ensemble that extends across the whole or a circumscribed area of the retinotopic mosaic. A second class of outputs from the lobula comprises wide-field neurons, the dendrites of which interact with planar fields or column-like patches of retinotopic inputs from the medulla. These neurons also send their axons to optic glomeruli. Dye fills demonstrate that lobula complex neurons supplying glomeruli do not generally terminate directly on descending neurons. Local interneurons and projection neurons provide integrative circuitry within and among glomeruli. As exemplified by the anterior optic tubercle, optic glomeruli can also have elaborate internal architectures. The results are discussed with respect to the identification of motion- and orientation-selective neurons at the level of the lobula and lateral protocerebrum and with respect to the evolutionary implications raised by the existence of neural arrangements serving the compound eyes, which are organized like neuropils serving segmental ganglia equipped with appendages.