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

Moving object detection based on bioinspired background subtraction

Flying insects rely mainly upon visual motion to detect and track objects. There has been a lot of research on fly inspired algorithms for object detection, but few have been developed based on visual motion alone. One of the daunting difficulties is that the neural and circuit mechanisms underlying the foreground-background segmentation are still unclear. Our previous modeling study proposed that the lobula held parallel pathways with distinct directional selectivity, each of which could retinotopically discriminate figures moving in its own preferred direction based on relative motion cues. The previous model, however, did not address how the multiple parallel pathways gave the only detection output at their common downstream. Since the preferred directions of the pathways along either horizontal or vertical axis were opposite to each other, the background moving in the opposite direction to an object also activated the corresponding lobula pathway. Indiscriminate or ungated projection from all the pathways to their downstream would mix objects with the moving background, making the previous model fail with non-stationary background. Here, we extend the previous model by proposing that the background motion-dependent gating of individual lobula projections is the key to object detection. Large-field lobula plate tangential cells are hypothesized to perform the gating to realize bioinspired background subtraction. The model is shown to be capable of implementing a robust detection of moving objects in video sequences with either a moving camera that induces translational optic flow or a static camera. The model sheds light on the potential of the concise fly algorithm in real-world applications.

Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons

Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.

A Closer Look at Histamine in Drosophila

The present work intends to provide a closer look at histamine in Drosophila. This choice is motivated firstly because Drosophila has proven over the years to be a very simple, but powerful, model organism abundantly assisting scientists in explaining not only normal functions, but also derangements that occur in higher organisms, not excluding humans. Secondly, because histamine has been demonstrated to be a pleiotropic master molecule in pharmacology and immunology, with increasingly recognized roles also in the nervous system. Indeed, it interacts with various neurotransmitters and controls functions such as learning, memory, circadian rhythm, satiety, energy balance, nociception, and motor circuits, not excluding several pathological conditions. In view of this, our review is focused on the knowledge that the use of Drosophila has added to the already vast histaminergic field. In particular, we have described histamine's actions on photoreceptors sustaining the visual system and synchronizing circadian rhythms, but also on temperature preference, courtship behavior, and mechanosensory transmission. In addition, we have highlighted the pathophysiological consequences of mutations on genes involved in histamine metabolism and signaling. By promoting critical discussion and further research, our aim is to emphasize and renew the importance of histaminergic research in biomedicine through the exploitation of Drosophila, hopefully extending the scientific debate to the academic, industry, and general public audiences.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Identifying different sleep stages in humans and other mammals has traditionally relied on electroencephalograms. Such an approach is not feasible in certain animals such as invertebrates, although these animals could also be sleeping in stages. Here, we perform long-term multichannel local field potential recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We acquired consistent spatial recordings of local field potentials across multiple flies, allowing us to compare brain activity across awake and sleep periods. Using machine learning, we uncover distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of microbehaviors associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Sleep is observed in most animals, which suggests it subserves a fundamental process associated with adaptive biological functions. However, the evidence to directly associate sleep with a specific function is lacking, in part because sleep is not a single process in many animals. In humans and other mammals, different sleep stages have traditionally been identified using electroencephalograms (EEGs), but such an approach is not feasible in different animals such as insects. Here, we perform long-term multichannel local field potential (LFP) recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We developed protocols to allow for consistent spatial recordings of LFPs across multiple flies, allowing us to compare the LFP activity across awake and sleep periods and further compare the same to induced sleep. Using machine learning, we uncover the existence of distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of micro-behaviours associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

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.

Neural mechanisms to exploit positional geometry for collision avoidance

Visual motion provides rich geometrical cues about the three-dimensional configuration of the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision-avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object and motion detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.

Multimodal Information Processing and Associative Learning in the Insect Brain

Simple Summary

Insect behaviors are a great indicator of evolution and provide useful information about the complexity of organisms. The realistic sensory scene of an environment is complex and replete with multisensory inputs, making the study of sensory integration that leads to behavior highly relevant. We summarize the recent findings on multimodal sensory integration and the behaviors that originate from them in our review.

Abstract

The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings.

Identifying Inputs to Visual Projection Neurons in Drosophila Lobula by Analyzing Connectomic Data

Electron microscopy (EM)-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of the lobula, a neuropil putatively dedicated to detecting object-like features, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity-based and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously undocumented connectivity between lobula input and output neurons. While future, more complete connectomic reconstructions are necessary to verify the results presented here, they can serve as a useful basis for formulating hypotheses on mechanisms of visual feature detection in lobula.

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours, but their applicability across sensory and task domains remains untested. Here, we assess the capacity of our previous model (Sun et al. 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference, providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly's head direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

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.

The lobula plate is exclusive to insects

Just one superorder of insects is known to possess a neuronal network that mediates extremely rapid reactions in flight in response to changes in optic flow. Research on the identity and functional organization of this network has over the course of almost half a century focused exclusively on the order Diptera, a member of the approximately 300-million-year-old clade Holometabola defined by its mode of development. However, it has been broadly claimed that the pivotal neuropil containing the network, the lobula plate, originated in the Cambrian before the divergence of Hexapoda and Crustacea from a mandibulate ancestor. This essay defines the traits that designate the lobula plate and argues against a homologue in Crustacea. It proposes that the origin of the lobula plate is relatively recent and may relate to the origin of flight.

The connectome of the adult Drosophila mushroom body provides insights into function

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory, and activity regulation. Here, we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

Vesicular neurotransmitter transporters in Drosophila melanogaster

Drosophila melanogaster express vesicular transporters for the storage of neurotransmitters acetylcholine, biogenic amines, GABA, and glutamate. The large array of powerful molecular-genetic tools available in Drosophila enhances the use of this model organism for studying transporter function and regulation.

Spatial readout of visual looming in the central brain of Drosophila

Visual systems can exploit spatial correlations in the visual scene by using retinotopy, the organizing principle by which neighboring cells encode neighboring spatial locations. However, retinotopy is often lost, such as when visual pathways are integrated with other sensory modalities. How is spatial information processed outside of strictly visual brain areas? Here, we focused on visual looming responsive LC6 cells in Drosophila, a population whose dendrites collectively cover the visual field, but whose axons form a single glomerulus-a structure without obvious retinotopic organization-in the central brain. We identified multiple cell types downstream of LC6 in the glomerulus and found that they more strongly respond to looming in different portions of the visual field, unexpectedly preserving spatial information. Through EM reconstruction of all LC6 synaptic inputs to the glomerulus, we found that LC6 and downstream cell types form circuits within the glomerulus that enable spatial readout of visual features and contralateral suppression-mechanisms that transform visual information for behavioral control.

Parallel Visual Pathways with Topographic versus Nontopographic Organization Connect the Drosophila Eyes to the Central Brain

One hallmark of the visual system is a strict retinotopic organization from the periphery toward the central brain, where functional imaging in Drosophila revealed a spatially accurate representation of visual cues in the central complex. This raised the question how, on a circuit level, the topographic features are implemented, as the majority of visual neurons enter the central brain converge in optic glomeruli. We discovered a spatial segregation of topographic versus nontopographic projections of distinct classes of medullo-tubercular (MeTu) neurons into a specific visual glomerulus, the anterior optic tubercle (AOTU). These parallel channels synapse onto different tubercular-bulbar (TuBu) neurons, which in turn relay visual information onto specific central complex ring neurons in the bulb neuropil. Hence, our results provide the circuit basis for spatially accurate representation of visual information and highlight the AOTU's role as a prominent relay station for spatial information from the retina to the central brain.

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A Drosophila visual circuit conveys input from the periphery to the central brain

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Several synaptic pathways form parallel channels using the anterior optic tubercle

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Some pathways maintain topographic relationships across several synaptic steps

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Different target neurons in the central brain are identified

Serotonergic modulation of visual neurons in Drosophila melanogaster

Sensory systems rely on neuromodulators, such as serotonin, to provide flexibility for information processing as stimuli vary, such as light intensity throughout the day. Serotonergic neurons broadly innervate the optic ganglia of Drosophila melanogaster, a widely used model for studying vision. It remains unclear whether serotonin modulates the physiology of interneurons in the optic ganglia. To address this question, we first mapped the expression patterns of serotonin receptors in the visual system, focusing on a subset of cells with processes in the first optic ganglion, the lamina. Serotonin receptor expression was found in several types of columnar cells in the lamina including 5-HT2B in lamina monopolar cell L2, required for spatiotemporal luminance contrast, and both 5-HT1A and 5-HT1B in T1 cells, whose function is unknown. Subcellular mapping with GFP-tagged 5-HT2B and 5-HT1A constructs indicated that these receptors localize to layer M2 of the medulla, proximal to serotonergic boutons, suggesting that the medulla neuropil is the primary site of serotonergic regulation for these neurons. Exogenous serotonin increased basal intracellular calcium in L2 terminals in layer M2 and modestly decreased the duration of visually induced calcium transients in L2 neurons following repeated dark flashes, but otherwise did not alter the calcium transients. Flies without functional 5-HT2B failed to show an increase in basal calcium in response to serotonin. 5-HT2B mutants also failed to show a change in amplitude in their response to repeated light flashes but other calcium transient parameters were relatively unaffected. While we did not detect serotonin receptor expression in L1 neurons, they, like L2, underwent serotonin-induced changes in basal calcium, presumably via interactions with other cells. These data demonstrate that serotonin modulates the physiology of interneurons involved in early visual processing in Drosophila.

Serotonergic neurons innervate the Drosophila melanogaster eye, but it was not known whether serotonin signaling could induce acute physiological responses in visual interneurons. We found serotonin receptors expressed in all neuropils of the optic lobe and identified specific neurons involved in visual information processing that express serotonin receptors. Activation of these receptors increased intracellular calcium in first order interneurons L1 and L2 and may enhance visually induced calcium transients in L2 neurons. These data support a role for the serotonergic neuromodulation of interneurons in the Drosophila visual system.

Non-canonical Receptive Field Properties and Neuromodulation of Feature-Detecting Neurons in Flies

Several fundamental aspects of motion vision circuitry are prevalent across flies and mice. Both taxa segregate ON and OFF signals. For any given spatial pattern, motion detectors in both taxa are tuned to speed, selective for one of four cardinal directions, and modulated by catecholamine neurotransmitters. These similarities represent conserved, canonical properties of the functional circuits and computational algorithms for motion vision. Less is known about feature detectors, including how receptive field properties differ from the motion pathway or whether they are under neuromodulatory control to impart functional plasticity for the detection of salient objects from a moving background. Here, we investigated 19 types of putative feature selective lobula columnar (LC) neurons in the optic lobe of the fruit fly Drosophila melanogaster to characterize divergent properties of feature selection. We identified LC12 and LC15 as feature detectors. LC15 encodes moving bars, whereas LC12 is selective for the motion of discrete objects, mostly independent of size. Neither is selective for contrast polarity, speed, or direction, highlighting key differences in the underlying algorithms for feature detection and motion vision. We show that the onset of background motion suppresses object responses by LC12 and LC15. Surprisingly, the application of octopamine, which is released during flight, reverses the suppressive influence of background motion, rendering both LCs able to track moving objects superimposed against background motion. Our results provide a comparative framework for the function and modulation of feature detectors and new insights into the underlying neuronal mechanisms involved in visual feature detection.

A new method of recording from the giant fiber of Drosophila melanogaster shows that the strength of its auditory inputs remains constant with age

There have been relatively few studies of how central synapses age in adult Drosophila melanogaster. In this study we investigate the aging of the synaptic inputs to the Giant Fiber (GF) from auditory Johnston's Organ neurons (JONs). In previously published experiments an indirect assay of this synaptic connection was used; here we describe a new, more direct assay, which allows reliable detection of the GF action potential in the neck connective, and long term recording of its responses to sound. Genetic poisoning using diphtheria toxin expressed in the GF with R68A06-GAL4 was used to confirm that this signal indeed arose from the GF and not from other descending neurons. As before, the sound-evoked action potentials (SEPs) in the antennal nerve were recorded via an electrode inserted at the base of the antenna. It was noted that an action potential in the GF elicited an antennal twitch, which in turn evoked a mechanosensory response from the JONs in the absence of sound. We then used these extracellular recording techniques in males and female of different ages to quantify the response of the JONs to a brief sound impulse, and also to measure the strength of the connection between the JONs and the GF. At no age was there any significant difference between males and females, for any of the parameters measured. The sensitivity of the JONs to a sound impulse approximately doubled between 1 d and 10 d after eclosion, which corresponds to the period when most mating is taking place. Subsequently JON sensitivity decreased with age, being approximately half as sensitive at 20 d and one-third as sensitive at 50 d, as compared to 10 d. However, the strength of the connection between the auditory input and the GF itself remained unchanged with age, although it did show some variability that could mask any small changes.

Drosophila Neuroscience: Should I Land or Should I Jump?

Information about behavioral states can be integrated in decision-making circuits. In Drosophila, the behavioral state - flying versus not flying - determines whether flies land or jump by dynamically coupling visual information to pre-motor descending neurons.

Neural circuitry of social learning in Drosophila requires multiple inputs to facilitate inter-species communication

Drosophila species communicate the threat of parasitoid wasps to naïve individuals. Communication of the threat between closely related species is efficient, while more distantly related species exhibit a dampened, partial communication. Partial communication between D. melanogaster and D. ananassae about wasp presence is enhanced following a period of cohabitation, suggesting that species-specific natural variations in communication 'dialects' can be learned through socialization. In this study, we identify six regions of the Drosophila brain essential for dialect training. We pinpoint subgroups of neurons in these regions, including motion detecting neurons in the optic lobe, layer 5 of the fan-shaped body, the D glomerulus in the antennal lobe, and the odorant receptor Or69a, where activation of each component is necessary for dialect learning. These results reveal functional neural circuits that underlie complex Drosophila social behaviors, and these circuits are required for integration several cue inputs involving multiple regions of the Drosophila brain.

Visual-Olfactory Integration in the Human Disease Vector Mosquito Aedes aegypti

Mosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify, and locate their hosts [1-4]. Although we increasingly know more about the role of chemosensory behaviors in mediating mosquito-host interactions [1], the role of visual cues is comparatively less studied [3], and how the combination of olfactory and visual information is integrated in the mosquito brain remains unknown. In the present study, we used a tethered-flight light-emitting diode (LED) arena, which allowed for quantitative control over the stimuli, and a control theoretic model to show that CO₂ modulates mosquito steering responses toward vertical bars. To gain insight into the neural basis of this olfactory and visual coupling, we conducted two-photon microscopy experiments in a new GCaMP6s-expressing mosquito line. Imaging revealed that neuropil regions within the lobula exhibited strong responses to objects, such as a bar, but showed little response to a large-field motion. Approximately 20% of the lobula neuropil we imaged were modulated when CO₂ preceded the presentation of a moving bar. By contrast, responses in the antennal (olfactory) lobe were not modulated by visual stimuli presented before or after an olfactory stimulus. Together, our results suggest that asymmetric coupling between these sensory systems provides enhanced steering responses to discrete objects.

Mushroom bodies in crustaceans: Insect-like organization in the caridid shrimp Lebbeus groenlandicus

Paired centers in the forebrain of insects, called the mushroom bodies, have become the most investigated brain region of any invertebrate due to novel genetic strategies that relate unique morphological attributes of these centers to their functional roles in learning and memory. Mushroom bodies possessing all the morphological attributes of those in dicondylic insects have been identified in mantis shrimps, basal hoplocarid crustaceans that are sister to Eumalacostraca, the most species-rich group of Crustacea. However, unless other examples of mushroom bodies can be identified in Eumalacostraca, the possibility is that mushroom body-like centers may have undergone convergent evolution in Hoplocarida and are unique to this crustacean lineage. Here, we provide evidence that speaks against convergent evolution, describing in detail the paired mushroom bodies in the lateral protocerebrum of a decapod crustacean, Lebbeus groenlandicus, a species belonging to the infraorder Caridea, an ancient lineage of Eumalacostraca.

A Single-Cell Level and Connectome-Derived Computational Model of the Drosophila Brain

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which (1) identifies the polarity of each neuron arbor, (2) predicts connections between neurons, (3) translates morphology data from the database into physiology parameters for computational modeling, (4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and (5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

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.

Two visual systems in one eyestalk: The unusual optic lobe metamorphosis in the stomatopod Alima pacifica

The compound eyes of adult stomatopod crustaceans have two to six ommatidial rows at the equator, called the midband, that are often specialized for color and polarization vision. Beneath the retina, this midband specialization is represented as enlarged optic lobe lamina cartridges and a hernia-like expansion in the medulla. We studied how the optic lobe transforms from the larvae, which possess typical crustacean larval compound eyes without a specialized midband, through metamorphosis into the adults with the midband in a two midband-row species Alima pacifica. Using histological staining, immunolabeling, and 3D reconstruction, we show that the last-stage stomatopod larvae possess double-retina eyes, in which the developing adult visual system forms adjacent to, but separate from, the larval visual system. Beneath the two retinas, the optic lobe also contains two sets of optic neuropils, comprising of a larval lamina, medulla, and lobula, as well as an adult lamina, medulla, and lobula. The larval eye and all larval optic neuropils degenerate and disappear approximately a week after metamorphosis. In stomatopods, the unique adult visual system and all optic neuropils develop alongside the larval system in the eyestalk of last-stage larvae, where two visual systems and two independent visual processing pathways coexist. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 3-14, 2018.

Feature Integration Drives Probabilistic Behavior in the Drosophila Escape Response

Animals rely on dedicated sensory circuits to extract and encode environmental features. How individual neurons integrate and translate these features into behavioral responses remains a major question. Here, we identify a visual projection neuron type that conveys predator approach information to the Drosophila giant fiber (GF) escape circuit. Genetic removal of this input during looming stimuli reveals that it encodes angular expansion velocity, whereas other input cell type(s) encode angular size. Motor program selection and timing emerge from linear integration of these two features within the GF. Linear integration improves size detection invariance over prior models and appropriately biases motor selection to rapid, GF-mediated escapes during fast looms. Our findings suggest feature integration, and motor control may occur as simultaneous operations within the same neuron and establish the Drosophila escape circuit as a model system in which these computations may be further dissected at the circuit level. VIDEO ABSTRACT.

Anatomy of the lobula complex in the brain of the praying mantis compared to the lobula complexes of the locust and cockroach

The praying mantis is an insect which relies on vision for capturing prey, avoiding being eaten and for spatial orientation. It is well known for its ability to use stereopsis for estimating the distance of objects. The neuronal substrate mediating visually driven behaviors, however, is not very well investigated. To provide a basis for future functional studies, we analyzed the anatomical organization of visual neuropils in the brain of the praying mantis Hierodula membranacea and provide supporting evidence from a second species, Rhombodera basalis, with particular focus on the lobula complex (LOX). Neuropils were three‐dimensionally reconstructed from synapsin‐immunostained whole mount brains. The neuropil organization and the pattern of γ‐aminobutyric acid immunostaining of the medulla and LOX were compared between the praying mantis and two related polyneopteran species, the Madeira cockroach and the desert locust. The investigated visual neuropils of the praying mantis are highly structured. Unlike in most insects the LOX of the praying mantis consists of five nested neuropils with at least one neuropil not present in the cockroach or locust. Overall, the mantis LOX is more similar to the LOX of the locust than the more closely related cockroach suggesting that the sensory ecology plays a stronger role than the phylogenetic distance of the three species in structuring this center of visual information processing.

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.

Anatomical organization of the brain of a diurnal and a nocturnal dung beetle

To avoid the fierce competition for food, South African ball-rolling dung beetles carve a piece of dung off a dung-pile, shape it into a ball and roll it away along a straight line path. For this unidirectional exit from the busy dung pile, at night and day, the beetles use a wide repertoire of celestial compass cues. This robust and relatively easily measurable orientation behavior has made ball-rolling dung beetles an attractive model organism for the study of the neuroethology behind insect orientation and sensory ecology. Although there is already some knowledge emerging concerning how celestial cues are processed in the dung beetle brain, little is known about its general neural layout. Mapping the neuropils of the dung beetle brain is thus a prerequisite to understand the neuronal network that underlies celestial compass orientation. Here, we describe and compare the brains of a day-active and a night-active dung beetle species based on immunostainings against synapsin and serotonin. We also provide 3D reconstructions for all brain areas and many of the fiber bundles in the brain of the day-active dung beetle. Comparison of neuropil structures between the two dung beetle species revealed differences that reflect adaptations to different light conditions. Altogether, our results provide a reference framework for future studies on the neuroethology of insects in general and dung beetles in particular.

Ring Attractor Dynamics Emerge from a Spiking Model of the Entire Protocerebral Bridge

Animal navigation is accomplished by a combination of landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca²⁺ correlates of landmark position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (CX; Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: (1) responsiveness to the position of external stimuli; (2) persistence in the absence of external stimuli; (3) locking onto a single external stimulus when presented with two competitors; (4) stochastically switching between competitors with low probability; and (5) sliding or jumping between positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogs of neuronal cell types in the PB (Lin et al., 2013; Wolff et al., 2015), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca²⁺ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the putative PB-EB ring attractor and the circuit dynamics phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than fine-scale biological detail.

Object-Detecting Neurons in Drosophila

Many animals rely on vision to detect objects such as conspecifics, predators, and prey. Hypercomplex cells found in feline cortex and small target motion detectors found in dragonfly and hoverfly optic lobes demonstrate robust tuning for small objects, with weak or no response to larger objects or movement of the visual panorama [1-3]. However, the relationship among anatomical, molecular, and functional properties of object detection circuitry is not understood. Here we characterize a specialized object detector in Drosophila, the lobula columnar neuron LC11 [4]. By imaging calcium dynamics with two-photon excitation microscopy, we show that LC11 responds to the omni-directional movement of a small object darker than the background, with little or no responses to static flicker, vertically elongated bars, or panoramic gratings. LC11 dendrites innervate multiple layers of the lobula, and each dendrite spans enough columns to sample 75° of visual space, yet the area that evokes calcium responses is only 20° wide and shows robust responses to a 2.2° object spanning less than half of one facet of the compound eye. The dendrites of neighboring LC11s encode object motion retinotopically, but the axon terminals fuse into a glomerular structure in the central brain where retinotopy is lost. Blocking inhibitory ionic currents abolishes small object sensitivity and facilitates responses to elongated bars and gratings. Our results reveal high-acuity object motion detection in the Drosophila optic lobe.

The eyes have it

Molecular genetic experiments are revealing how the fly brain generates behavioral responses to visual stimuli.

Visual projection neurons in the Drosophila lobula link feature detection to distinct behavioral programs

Visual projection neurons (VPNs) provide an anatomical connection between early visual processing and higher brain regions. Here we characterize lobula columnar (LC) cells, a class of Drosophila VPNs that project to distinct central brain structures called optic glomeruli. We anatomically describe 22 different LC types and show that, for several types, optogenetic activation in freely moving flies evokes specific behaviors. The activation phenotypes of two LC types closely resemble natural avoidance behaviors triggered by a visual loom. In vivo two-photon calcium imaging reveals that these LC types respond to looming stimuli, while another type does not, but instead responds to the motion of a small object. Activation of LC neurons on only one side of the brain can result in attractive or aversive turning behaviors depending on the cell type. Our results indicate that LC neurons convey information on the presence and location of visual features relevant for specific behaviors.

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

Evidence for selective attention in the insect brain

The capacity for selective attention appears to be required by any animal responding to an environment containing multiple objects, although this has been difficult to study in smaller animals such as insects. Clear operational characteristics of attention however make study of this crucial brain function accessible to any animal model. Whereas earlier approaches have relied on freely behaving paradigms placed in an ecologically relevant context, recent tethered preparations have focused on brain imaging and electrophysiology in virtual reality environments. Insight into brain activity during attention-like behavior has revealed key elements of attention in the insect brain. Surprisingly, a variety of brain structures appear to be involved, suggesting that even in the smallest brains attention might involve widespread coordination of neural activity.

Direct neural pathways convey distinct visual information to Drosophila mushroom bodies

Previously, we demonstrated that visual and olfactory associative memories of Drosophila share mushroom body (MB) circuits (Vogt et al., 2014). Unlike for odor representation, the MB circuit for visual information has not been characterized. Here, we show that a small subset of MB Kenyon cells (KCs) selectively responds to visual but not olfactory stimulation. The dendrites of these atypical KCs form a ventral accessory calyx (vAC), distinct from the main calyx that receives olfactory input. We identified two types of visual projection neurons (VPNs) directly connecting the optic lobes and the vAC. Strikingly, these VPNs are differentially required for visual memories of color and brightness. The segregation of visual and olfactory domains in the MB allows independent processing of distinct sensory memories and may be a conserved form of sensory representations among insects.

DOI:http://dx.doi.org/10.7554/eLife.14009.001

Shaking B Mediates Synaptic Coupling between Auditory Sensory Neurons and the Giant Fiber of Drosophila melanogaster

The Johnston’s Organ neurons (JONs) form chemical and electrical synapses onto the giant fiber neuron (GF), as part of the neuronal circuit that mediates the GF escape response in Drosophila melanogaster. The purpose of this study was to identify which of the 8 Drosophila innexins (invertebrate gap junction proteins) mediates the electrical connection at this synapse. The GF is known to express Shaking B (ShakB), specifically the ShakB(N+16) isoform only, at its output synapses in the thorax. The shakB² mutation disrupts these GF outputs and also abolishes JON-GF synaptic transmission. However, the identity of the innexin that forms the presynaptic hemichannels in the JONs remains unknown. We used electrophysiology, immunocytochemistry and dye injection, along with presynaptically-driven RNA interference, to investigate this question. The amplitude of the compound action potential recorded in response to sound from the base of the antenna (sound-evoked potential, or SEP) was reduced by RNAi of the innexins Ogre, Inx3, Inx6 and, to a lesser extent Inx2, suggesting that they could be required in JONs for proper development, excitability, or synchronization of action potentials. The strength of the JON-GF connection itself was reduced to background levels only by RNAi of shakB, not of the other seven innexins. ShakB knockdown prevented Neurobiotin coupling between GF and JONs and removed the plaques of ShakB protein immunoreactivity that are present at the region of contact. Specific shakB RNAi lines that are predicted to target the ShakB(L) or ShakB(N) isoforms alone did not reduce the synaptic strength, implying that it is ShakB(N+16) that is required in the presynaptic neurons. Overexpression of ShakB(N+16) in JONs caused the formation of ectopic dye coupling, whereas ShakB(N) prevented it altogether, supporting this conclusion and also suggesting that gap junction proteins may have an instructive role in synaptic target choice.

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.

From the Eye to the Brain: Development of the Drosophila Visual System

How stem cells produce the huge diversity of neurons that form the visual system, and how these cells are assembled in neural circuits are a critical question in developmental neurobiology. Investigations in Drosophila have led to the discovery of several basic principles of neural patterning. In this chapter, we provide an overview of the field by describing the development of the Drosophila visual system, from the embryo to the adult and from the gross anatomy to the cellular level. We then explore the general molecular mechanisms identified that might apply to other neural structures in flies or in vertebrates. Finally, we discuss the major challenges that remain to be addressed in the field.

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules' local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly's entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel's model integration by combining independently developed models of the retina and lamina neuropils in the fly's visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel's ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel's communication performance both over the number of interface ports exposed by an emulation's constituent modules and the total number of modules comprised by an emulation.

Cellular evidence for efference copy in Drosophila visuomotor processing

Each time a locomoting fly turns, the visual image sweeps over the retina and generates a motion stimulus. Classic behavioral experiments suggested that flies use active neural-circuit mechanisms to suppress the perception of self-generated visual motion during intended turns. Direct electrophysiological evidence, however, has been lacking. We found that visual neurons in Drosophila receive motor-related inputs during rapid flight turns. These inputs arrived with a sign and latency appropriate for suppressing each targeted cell's visual response to the turn. Precise measurements of behavioral and neuronal response latencies supported the idea that motor-related inputs to optic flow-processing cells represent internal predictions of the expected visual drive induced by voluntary turns. Motor-related inputs to small object-selective visual neurons could reflect either proprioceptive feedback from the turn or internally generated signals. Our results in Drosophila echo the suppression of visual perception during rapid eye movements in primates, demonstrating common functional principles of sensorimotor processing across phyla.

Neurons forming optic glomeruli compute figure-ground discriminations in Drosophila

Many animals rely on visual figure-ground discrimination to aid in navigation, and to draw attention to salient features like conspecifics or predators. Even figures that are similar in pattern and luminance to the visual surroundings can be distinguished by the optical disparity generated by their relative motion against the ground, and yet the neural mechanisms underlying these visual discriminations are not well understood. We show in flies that a diverse array of figure-ground stimuli containing a motion-defined edge elicit statistically similar behavioral responses to one another, and statistically distinct behavioral responses from ground motion alone. From studies in larger flies and other insect species, we hypothesized that the circuitry of the lobula--one of the four, primary neuropiles of the fly optic lobe--performs this visual discrimination. Using calcium imaging of input dendrites, we then show that information encoded in cells projecting from the lobula to discrete optic glomeruli in the central brain group these sets of figure-ground stimuli in a homologous manner to the behavior; "figure-like" stimuli are coded similar to one another and "ground-like" stimuli are encoded differently. One cell class responds to the leading edge of a figure and is suppressed by ground motion. Two other classes cluster any figure-like stimuli, including a figure moving opposite the ground, distinctly from ground alone. This evidence demonstrates that lobula outputs provide a diverse basis set encoding visual features necessary for figure detection.