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The ability to drive expression of exogenous genes in different tissues and cell types, under the control of specific enhancers, has been crucial for discovery in biology. While many enhancers drive expression broadly, several genetic tools were developed to obtain access to isolated cell types. Studies of spatially organized neuropiles in the central nervous system of fruit flies have raised the need for a system that targets subsets of cells within a single neuronal type, a feat currently dependent on stochastic flip-out methods. To access the same cells within a given expression pattern consistently across fruit flies, we developed the light-gated expression system LOV-LexA. We combined the bacterial LexA transcription factor with the plant-derived light, oxygen, or voltage photosensitive domain and a fluorescent protein. Exposure to blue light uncages a nuclear localizing signal in the C-terminal of the light, oxygen, or voltage domain and leads to the translocation of LOV-LexA to the nucleus, with the subsequent initiation of transcription. LOV-LexA enables spatial and temporal control of expression of transgenes under LexAop sequences in larval fat body and pupal and adult neurons with blue light. The LOV-LexA tool is ready to use with GAL4 and Split-GAL4 drivers in its current form and constitutes another layer of intersectional genetics that provides light-controlled genetic access to specific cells across flies.

Nonlinear, multiplication-like operations carried out by individual nerve cells greatly enhance the computational power of a neural system

Visual animals detect spatial variations of light intensity and wavelength composition. Opponent coding is a common strategy for reducing information redundancy. Neurons equipped with both spatial and spectral opponency have been identified in vertebrates but not yet in insects. The Drosophila amacrine neuron Dm8 was recently reported to show color opponency. Here, we demonstrate Dm8 exhibits spatio-chromatic opponency. Antagonistic convergence of the direct input from the UV-sensing R7s and indirect input from the broadband receptors R1–R6 through Tm3 and Mi1 is sufficient to confer Dm8’s UV/Vis (ultraviolet/visible light) opponency. Using high resolution monochromatic stimuli, we show the pale and yellow subtypes of Dm8s, inheriting retinal mosaic characteristics, have distinct spectral tuning properties. Using 2D white-noise stimulus and reverse correlation analysis, we found that the UV receptive field (RF) of Dm8 has a center-inhibition/surround-excitation structure. In the absence of UV-sensing R7 inputs, the polarity of the RF is inverted owing to the excitatory input from the broadband photoreceptors R1–R6. Using a new synGRASP method based on endogenous neurotransmitter receptors, we show that neighboring Dm8s form mutual inhibitory connections mediated by the glutamate-gated chloride channel GluClα, which is essential for both Dm8’s spatial opponency and animals’ phototactic behavior. Our study shows spatio-chromatic opponency could arise in the early visual stage, suggesting a common information processing strategy in both invertebrates and vertebrates.

Electrical synapses are present in almost all organisms that have a nervous system. However, their brain-wide expression patterns and the full range of contributions to neural function are unknown in most species. Here, we first provide a light-microscopic, immunohistochemistry-based anatomical map of all innexin gap junction proteins-the building blocks of electrical synapses-in the central nervous system of Drosophila melanogaster. Of those innexin types that are expressed in the nervous system, some localize to glial cells, whereas others are predominantly expressed in neurons, with shakB being the most widely expressed neuronal innexin. We then focus on the function of shakB in VS/HS cells-a class of visual projection neurons-thereby uncovering an unexpected role for electrical synapses. Removing shakB from these neurons leads to spontaneous, cell-autonomous voltage and calcium oscillations, demonstrating that electrical synapses are required for these cells' intrinsic stability. Furthermore, we investigate the role of shakB-type electrical synapses in early visual processing. We find that the loss of shakB from the visual circuits upstream of VS/HS cells differentially impairs ON and OFF visual motion processing pathways but is not required for the computation of direction selectivity per se. Taken together, our study demonstrates that electrical synapses are widespread across the Drosophila nervous system and that they play essential roles in neuronal function and visual information processing.

Visual motion detection is among the best understood neuronal computations. As extensively investigated in tethered flies, visual motion signals are assumed to be crucial to detect and counteract involuntary course deviations. During free flight, however, course changes are also signalled by other sensory systems. Therefore, it is as yet unclear to what extent motion vision contributes to course control. To address this question, we genetically rendered flies motion-blind by blocking their primary motion-sensitive neurons and quantified their free-flight performance. We found that such flies have difficulty maintaining a straight flight trajectory, much like unimpaired flies in the dark. By unilateral wing clipping, we generated an asymmetry in propulsive force and tested the ability of flies to compensate for this perturbation. While wild-type flies showed a remarkable level of compensation, motion-blind animals exhibited pronounced circling behaviour. Our results therefore directly confirm that motion vision is necessary to fly straight under realistic conditions.

Neurotransmitter receptors and ion channels shape the biophysical properties of neurons, from the sign of the response mediated by neurotransmitter receptors to the dynamics shaped by voltage-gated ion channels. Therefore, knowing the localizations and types of receptors and channels present in neurons is fundamental to our understanding of neural computation. Here, we developed two approaches to visualize the subcellular localization of specific proteins in Drosophila: The flippase-dependent expression of GFP-tagged receptor subunits in single neurons and ‘FlpTag’, a versatile new tool for the conditional labelling of endogenous proteins. Using these methods, we investigated the subcellular distribution of the receptors GluClα, Rdl, and Dα7 and the ion channels para and Ih in motion-sensing T4/T5 neurons of the Drosophila visual system. We discovered a strictly segregated subcellular distribution of these proteins and a sequential spatial arrangement of glutamate, acetylcholine, and GABA receptors along the dendrite that matched the previously reported EM-reconstructed synapse distributions.

Summary Sensory systems need to reliably extract information from highly variable natural signals. Flies, for instance, use optic flow to guide their course and are remarkably adept at estimating image velocity regardless of image statistics. Current circuit models, however, cannot account for this robustness. Here, we demonstrate that the Drosophila visual system reduces input variability by rapidly adjusting its sensitivity to local contrast conditions. We exhaustively map functional properties of neurons in the motion detection circuit and find that local responses are compressed by surround contrast. The compressive signal is fast, integrates spatially, and derives from neural feedback. Training convolutional neural networks on estimating the velocity of natural stimuli shows that this dynamic signal compression can close the performance gap between model and organism. Overall, our work represents a comprehensive mechanistic account of how neural systems attain the robustness to carry out survival-critical tasks in challenging real-world environments.

Direction-selective T4/T5 neurons exist in four subtypes, each tuned to visual motion along one of the four cardinal directions. Along with their directional tuning, neurons of each T4/T5 subtype orient their dendrites and project their axons in a subtype-specific manner. Directional tuning, thus, appears strictly linked to morphology in T4/T5 neurons. How the four T4/T5 subtypes acquire their distinct morphologies during development remains largely unknown. Here, we investigated when and how the dendrites of the four T4/T5 subtypes acquire their specific orientations, and profiled the transcriptomes of all T4/T5 neurons during this process. This revealed a simple and stable combinatorial code of transcription factors defining the four T4/T5 subtypes during their development. Changing the combination of transcription factors of specific T4/T5 subtypes resulted in predictable and complete conversions of subtype-specific properties, i.e. dendrite orientation and matching axon projection pattern. Therefore, a combinatorial code of transcription factors coordinates the development of dendrite and axon morphologies to generate anatomical specializations that differentiate subtypes of T4/T5 motion-sensing neurons., Summary: Morphological and transcriptomic analyses allowed the identification of a combinatorial code of transcription factors that controls the development of subtype-specific morphologies in motion-detecting neurons of the Drosophila visual system.

Vision is an important sensory modality for navigation in roaming animals. In contrast to most vertebrates, insects usually must cope with low resolution retinal images and the inability to infer spatial features using accommodation or stereovision. However, during locomotion, the retinal input is dominated by characteristic panoramic image shifts, termed optic flow, that depend on self-motion parameters and environmental features. Therefore, optic flow provides a rich source of information guiding locomotion speed as well as the position and orientation of animals over time relative to their surroundings. Here, focusing on flight behavior, we describe the strategies and putative underlying neuronal mechanisms by which insects control their course through processing of visual motion cues.

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior., Author summary Survival-critical behaviors shape neural circuits to translate sensory information into strikingly fast predictions, e.g. in escaping from a predator faster than the system’s processing delay. We show that the fly visual system implements fast and accurate prediction of its visual experience. This provides crucial information for directing fast evasive maneuvers that unfold over just 40ms. Our work shows how this fast prediction is implemented, mechanistically, and suggests the existence of a novel sensory-motor pathway from the fly visual system to a wing steering motor neuron. Echoing and amplifying previous work in the retina, our work hypothesizes that the efficient encoding of predictive information is a universal design principle supporting fast, natural behaviors.

The reliable estimation of motion across varied surroundings represents a survival-critical task for sighted animals. How neural circuits have adapted to the particular demands of natural environments, however, is not well understood. We explored this question in the visual system of Drosophila melanogaster. Here, as in many mammalian retinas, motion is computed in parallel streams for brightness increments (ON) and decrements (OFF). When genetically isolated, ON and OFF pathways proved equally capable of accurately matching walking responses to realistic motion. To our surprise, detailed characterization of their functional tuning properties through in vivo calcium imaging and electrophysiology revealed stark differences in temporal tuning between ON and OFF channels. We trained an in silico motion estimation model on natural scenes and discovered that our optimized detector exhibited differences similar to those of the biological system. Thus, functional ON-OFF asymmetries in fly visual circuitry may reflect ON-OFF asymmetries in natural environments.

Estimating motion is a fundamental task for the visual system of sighted animals. In Drosophila, direction-selective T4 and T5 cells respond to moving brightness increments (ON) and decrements (OFF), respectively. Current algorithmic models of the circuit are based on the interaction of two differentially filtered signals. However, electron microscopy studies have shown that T5 cells receive their major input from four classes of neurons: Tm1, Tm2, Tm4, and Tm9. Using two-photon calcium imaging, we demonstrate that T5 is the first direction-selective stage within the OFF pathway. The four cells provide an array of spatiotemporal filters to T5. Silencing their synaptic output in various combinations, we find that all input elements are involved in OFF motion detection to varying degrees. Our comprehensive survey challenges the simplified view of how neural systems compute the direction of motion and suggests that an intricate interplay of many signals results in direction selectivity.

A neuron is conventionally regarded as a single processing unit. It receives input from one or several presynaptic cells, transforms these signals, and transmits one output signal to its postsynaptic partners. Exceptions exist: amacrine cells in the mamma- lian retina [1-3] or interneurons in the locust meso- thoracic ganglion [4] are thought to represent many electrically isolated microcircuits within one neuron. An extreme case of such an amacrine cell has recently been described in the Drosophila visual system. This cell, called CT1, reaches into two neuropils of the optic lobe, where it visits each of 700 repetitive columns, thereby covering the whole visual field [5, 6]. Due to its unusual morphology, CT1 has been suspected to perform local computations [6, 7], but this has never been proven. Using 2-photon calcium imaging and visual stimulation, we find highly compartmentalized retinotopic response properties in neighboring terminals of CT1, with each terminal acting as an independent functional unit. Model simulations demonstrate that this extreme case of compartmentalization is at the biophysical limit of neural computation.

In the Drosophila visual system, T4/T5 neurons represent the first stage of computation of the direction of visual motion. T4 and T5 neurons exist in four subtypes, each responding to motion in one of the four cardinal directions and projecting axons into one of the four lobula plate layers. However, all T4/T5 neurons share properties essential for sensing motion. How T4/T5 neurons acquire their properties during development is poorly understood. We reveal that the transcription factors SoxN and Sox102F control the acquisition of properties common to all T4/T5 neuron subtypes, i.e. the layer specificity of dendrites and axons. Accordingly, adult flies are motion blind after disruption of SoxN or Sox102F in maturing T4/T5 neurons. We further find that the transcription factors Ato and Dac are redundantly required in T4/T5 neuron progenitors for SoxN and Sox102F expression in T4/T5 neurons, linking the transcriptional programmes specifying progenitor identity to those regulating the acquisition of morphological properties in neurons. Our work will help to link structure, function and development in a neuronal type performing a computation that is conserved across vertebrate and invertebrate visual systems., Summary: RNA interference identifies SoxN and Sox102F as key regulators of the morphological properties of a neuronal type of the fruit fly visual system that computes the direction of motion.

Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond to visual stimuli moving in one but not in the opposite direction, so-called ‘direction-selective’ neurons, are found abundantly. In general, direction selectivity can arise by either signal amplification for stimuli moving in the cell’s preferred direction (‘preferred direction enhancement’), signal suppression for stimuli moving along the opposite direction (‘null direction suppression’), or a combination of both. While signal suppression can be readily implemented in biophysical terms by a hyperpolarization followed by a rectification corresponding to the nonlinear voltage-dependence of the Calcium channel, the biophysical mechanism for signal amplification has remained unclear so far. Taking inspiration from the fly, I analyze a neural circuit where a direction-selective ON-cell receives inhibitory input from an OFF cell on the preferred side of the dendrite, while excitatory ON-cells contact the dendrite centrally. This way, an ON edge moving along the cell’s preferred direction suppresses the inhibitory input, leading to a release from inhibition in the postsynaptic cell. The benefit of such a two-fold signal inversion lies in the resulting increase of the postsynaptic cell’s input resistance, amplifying its response to a subsequent excitatory input signal even with a passive dendrite, i.e. without voltage-gated ion channels. A motion detector implementing this mechanism together with null direction suppression shows a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio., Author summary Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond preferentially to visual stimuli moving in a certain direction are found abundantly. However, directional information is not represented at the level of single photoreceptors but rather has to be computed by subsequent neural circuits. Algorithmic models have been proposed in the past that calculate the direction of motion by multiplying and/or dividing the input signals from neighboring photoreceptors after asymmetric temporal filtering. But how can neurons multiply or divide? Inspired by recent data from fly motion-sensitive neurons, I present a biophysical model of a nerve cell that is based on purely passive conductance changes. I show that such a model can reveal a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio.

SummaryWhen navigating in their environment, animals use visual motion cues as feedback signals that are elicited by their own motion. Such signals are provided by wide-field neurons sampling motion directions at multiple image points as the animal maneuvers. Each one of these neurons responds selectively to a specific optic flow-field representing the spatial distribution of motion vectors on the retina. Here, we describe the discovery of a group of local, inhibitory interneurons in the fruit fly Drosophila key for filtering these cues. Using anatomy, molecular characterization, activity manipulation, and physiological recordings, we demonstrate that these interneurons convey direction-selective inhibition to wide-field neurons with opposite preferred direction and provide evidence for how their connectivity enables the computation required for integrating opposing motions. Our results indicate that, rather than sharpening directional selectivity per se, these circuit elements reduce noise by eliminating non-specific responses to complex visual information.

With the advent of neurogenetic methods, the neural basis of behavior is presently being analyzed in more and more detail. This is particularly true for visually driven behavior of Drosophila melanogaster where cell-specific driver lines exist that, depending on the combination with appropriate effector genes, allow for targeted recording, silencing and optogenetic stimulation of individual cell-types. Together with detailed connectomic data of large parts of the fly optic lobe, this has recently led to much progress in our understanding of the neural circuits underlying local motion detection. However, how such local information is combined by optic flow sensitive large-field neurons is still incompletely understood. Here, we aim to fill this gap by a dense reconstruction of lobula plate tangential cells of the fly lobula plate. These neurons collect input from many hundreds of local motion-sensing T4/T5 neurons and connect them to descending neurons or central brain areas. We confirm all basic features of HS and VS cells as published previously from light microscopy. In addition, we identified the dorsal and the ventral centrifugal horizontal, dCH and vCH cell, as well as three VSlike cells, including their distinct dendritic and axonal projection area.

In the fruit fly optic lobe, T4 and T5 cells represent the first direction-selective neurons, with T4 cells responding selectively to moving brightness increments (ON) and T5 cells to brightness decrements (OFF). Both T4 and T5 cells comprise four subtypes with directional tuning to one of the four cardinal directions. We had previously found that upward-sensitive T4 cells implement both preferred direction enhancement and null direction suppression (Haag et al., 2016). Here, we asked whether this mechanism generalizes to OFF-selective T5 cells and to all four subtypes of both cell classes. We found that all four subtypes of both T4 and T5 cells implement both mechanisms, that is preferred direction enhancement and null direction inhibition, on opposing sides of their receptive fields. This gives rise to the high degree of direction selectivity observed in both T4 and T5 cells within each subpopulation.

The fly visual system offers a unique opportunity to explore computations performed by single neurons. Two previous studies characterized, in vivo, the receptive field (RF) of the vertical system (VS) cells of the blowfly (calliphora vicina), both intracellularly in the axon, and, independently using Ca2+ imaging, in hundreds of distal dendritic branchlets. We integrated this information into detailed passive cable and compartmental models of 3D reconstructed VS cells. Within a given VS cell type, the transfer resistance (TR) from different branchlets to the axon differs substantially, suggesting that they contribute unequally to the shaping of the axonal RF. Weighting the local RFs of all dendritic branchlets by their respective TR yielded a faithful reproduction of the axonal RF. The model also predicted that the various dendritic branchlets are electrically decoupled from each other, thus acting as independent local functional subunits. The study suggests that single neurons in the fly visual system filter dendritic noise and compute the weighted average of their inputs.

Optogenetic channels and ion pumps have become indispensable tools in neuroscience to manipulate neuronal activity and thus to establish synaptic connectivity and behavioral causality. Inhibitory channels are particularly advantageous to explore signal processing in neural circuits since they permit the functional removal of selected neurons on a trial-by-trial basis. However, applying these tools to study the visual system poses a considerable challenge because the illumination required for their activation usually also stimulates photoreceptors substantially, precluding the simultaneous probing of visual responses. Here, we explore the utility of the recently discovered anion channelrhodopsins GtACR1 and GtACR2 for application in the visual system of Drosophila. We first characterized their properties using a larval crawling assay. We further obtained whole-cell recordings from cells expressing GtACR1, which mediated strong and light-sensitive photocurrents. Finally, using physiological recordings and a behavioral readout, we demonstrate that GtACR1 enables the fast and reversible silencing of genetically targeted neurons within circuits engaged in visual processing.

Images projected onto the retina of an animal eye are rarely still. Instead, they usually contain motion signals originating either from moving objects or from retinal slip caused by self-motion. Accordingly, motion signals tell the animal in which direction a predator, prey, or the animal itself is moving. At the neural level, visual motion detection has been proposed to extract directional information by a delay-and-compare mechanism, representing a classic example of neural computation. Neurons responding selectively to motion in one but not in the other direction have been identified in many systems, most prominently in the mammalian retina and the fly optic lobe. Technological advances have now allowed researchers to characterize these neurons’ upstream circuits in exquisite detail. Focusing on these upstream circuits, we review and compare recent progress in understanding the mechanisms that generate direction selectivity in the early visual system of mammals and flies.

The identification of neurotransmitter type used by a neuron is important for the functional dissection of neuronal circuits. In the model organism Drosophila melanogaster, several methods for discerning the neurotransmitter systems are available. Here, we expanded the toolbox for the identification of cholinergic neurons by generating a new line FRT-STOP-FRT-VAChT::HA that is a conditional tagged knock-in of the vesicular acetylcholine transporter (VAChT) gene in its endogenous locus. Importantly, in comparison to already available tools for the detection of cholinergic neurons, the FRT-STOP-FRT-VAChT::HA allele also allows for identification of the subcellular localization of the cholinergic presynaptic release sites in a cell-specific manner. We used the newly generated FRT-STOP-FRT-VAChT::HA line to characterize the Mi1 and Tm3 neurons in the fly visual system and found that VAChT is present in the axons of both cell types, suggesting that Mi1 and Tm3 neurons provide cholinergic input to the elementary motion detectors, the T4 neurons., Summary: A new transgenic Drosophila melanogaster line for the cell-type-specific identification of cholinergic release sites expands the available methods toolbox for discerning the neurotransmitter systems in the fly nervous system.

Super-resolution microscopy is a very powerful tool to investigate fine cellular structures and molecular arrangements in biological systems. For instance, stimulated emission depletion (STED) microscopy has been successfully used in recent years to investigate the arrangement and colocalization of different protein species in cells in culture and on the surface of specimens. However, because of its extreme sensitivity to light scattering, super-resolution imaging deep inside tissues remains a challenge. Here, we describe the preparation of thin slices from the fruit fly (Drosophila melanogaster) brain, subsequent immunolabeling and imaging with STED microscopy. This protocol allowed us to image small dendritic branches from neurons located deep in the fly brain with improved resolution compared with conventional light microscopy.

Understanding how the brain controls behaviour is undisputedly one of the grand goals of neuroscience research, and the pursuit of this goal has a long tradition in insect neuroscience. However, appropriate techniques were lacking for a long time. Recent advances in genetic and recording techniques now allow the participation of identified neurons in the execution of specific behaviours to be interrogated. By focusing on fly visual course control, I highlight what has been learned about the neuronal circuit modules that control visual guidance in Drosophila melanogaster through the use of these techniques.

Dendritic integration is a fundamental element of neuronal information processing. So far, few studies have provided a detailed spatial picture of this process, describing the properties of local dendritic activity and its subcellular organization. Here, we used 2-photon calcium imaging in optic flow processing neurons of the fly Calliphora vicina to determine the preferred location and direction of local motion cues for small branchlets throughout the entire dendrite. We found a pronounced retinotopic mapping on both the subcellular and the cell population level. In addition, dendritic branchlets residing in different layers of the neuropil were tuned to distinct directions of motion. Summing the local receptive fields of all dendritic branchlets reproduced the characteristic properties of these neurons' axonal output receptive fields. Our results corroborate the notion that the dendritic morphology of vertical system cells allows them to selectively collect local motion inputs with particular directional preferences from a spatially organized input repertoire, thus forming filters that match global patterns of optic flow. Furthermore, we suggest that the facet arrangement across the fly's eye shapes the subcellular direction tuning to local motion stimuli. These data illustrate a highly structured circuit organization as an efficient way to hard-wire a complex sensory task.

Detecting the direction of image motion is a fundamental component of visual computation and is essential for survival of the animal. However, at the level of the photoreceptors, the direction in which the image is shifting locally is not explicitly represented. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring photoreceptors over time. The exact nature of this process as implemented in the Drosophila visual system is currently being studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information in this species.

Visual systems extract directional motion information from spatiotemporal luminance changes on the retina. An algorithmic model, the Reichardt detector, accounts for this by multiplying adjacent inputs after asymmetric temporal filtering. The outputs of two mirror-symmetrical units tuned to opposite directions are thought to be subtracted on the dendrites of wide-field motion-sensitive lobula plate tangential cells by antagonistic transmitter systems. InDrosophila, small-field T4/T5 cells carry visual motion information to the tangential cells that are depolarized during preferred and hyperpolarized during null direction motion. While preferred direction input is likely provided by excitation from T4/T5 terminals, the origin of null direction inhibition is unclear. Probing the connectivity between T4/T5 and tangential cells inDrosophilausing a combination of optogenetics, electrophysiology, and pharmacology, we found a direct excitatory as well as an indirect inhibitory component. This suggests that the null direction response is caused by feedforward inhibition via yet unidentified neurons.

Seeing the direction of motion is fundamental for visual navigation, predator avoidance, and prey capture. However, the direction of motion is not explicitly represented at the level of individual photoreceptors. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring photoreceptors over time. The exact nature of this process as implemented in the Drosophila visual system is currently being studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information in this species.

When confronted with a large-field stimulus rotating around the vertical body axis, flies display a following behavior called “optomotor response.” As neural control elements, the large tangential horizontal system (HS) cells of the lobula plate have been prime candidates for long. Here, we applied optogenetic stimulation of HS cells to evaluate their behavioral role inDrosophila. To minimize interference of the optical activation of channelrhodopsin-2 with the visual perception of the flies, we used a bistable variant called ChR2-C128S. By applying pulses of blue and yellow light, we first demonstrate electrophysiologically that lobula plate tangential cells can be activated and deactivated repeatedly with no evident change in depolarization strength over trials. We next show that selective optogenetic activation of HS cells elicits robust yaw head movements and yaw turning responses in fixed and tethered flying flies, respectively.

Detecting the direction of motion contained in the visual scene is crucial for many behaviors. However, because single photoreceptors only signal local luminance changes, motion detection requires a comparison of signals from neighboring photoreceptors across time in downstream neuronal circuits. For signals to coincide on readout neurons that thus become motion and direction selective, different input lines need to be delayed with respect to each other. Classical models of motion detection rely on non-linear interactions between two inputs after different temporal filtering. However, recent studies have suggested the requirement for at least three, not only two, input signals. Here, we comprehensively characterize the spatiotemporal response properties of all columnar input elements to the elementary motion detectors in the fruit fly, T4 and T5 cells, via two-photon calcium imaging. Between these input neurons, we find large differences in temporal dynamics. Based on this, computer simulations show that only a small subset of possible arrangements of these input elements maps onto a recently proposed algorithmic three-input model in a way that generates a highly direction-selective motion detector, suggesting plausible network architectures. Moreover, modulating the motion detection system by octopamine-receptor activation, we find the temporal tuning of T4 and T5 cells to be shifted toward higher frequencies, and this shift can be fully explained by the concomitant speeding of the input elements.

Drosophila has emerged as an important model organism for the study of the neural basis of behavior. Its main asset is the experimental accessibility of identified neurons by genetic manipulation and physiological recordings. Drosophila therefore offers the opportunity to reach an integrative understanding of the development and neural underpinnings of behavior at all processing stages, from sensing to motor control, in a single species. Here, we will provide an account of the procedures involved in recording the electrical potential of individual neurons in the visual system of adult Drosophila using the whole-cell patch-clamp method. To this end, animals are fixed to a holder and mounted below a recording chamber. The head capsule is cut open and the glial sheath covering the brain is ruptured by a combination of shearing and enzymatic digest. Neuronal somata are thus exposed and targeted by low-resistance patch electrodes. After formation of a high resistance seal, electrical access to the cell is gained by small current pulses and suction. Stable recordings of large neurons are feasible for1 h and can be combined with controlled visual stimulation as well as genetic and pharmacological manipulation of upstream circuit elements to infer circuit function in great detail.

How neurons become sensitive to the direction of visual motion represents a classic example of neural computation. Two alternative mechanisms have been discussed in the literature so far: preferred direction enhancement, by which responses are amplified when stimuli move along the preferred direction of the cell, and null direction suppression, where one signal inhibits the response to the subsequent one when stimuli move along the opposite, i.e. null direction. Along the processing chain in the Drosophila optic lobe, directional responses first appear in T4 and T5 cells. Visually stimulating sequences of individual columns in the optic lobe with a telescope while recording from single T4 neurons, we find both mechanisms at work implemented in different sub-regions of the receptive field. This finding explains the high degree of directional selectivity found already in the fly’s primary motion-sensing neurons and marks an important step in our understanding of elementary motion detection. DOI: http://dx.doi.org/10.7554/eLife.17421.001, eLife digest The brain extracts information from signals delivered from the eyes and other sensory organs in order to direct behavior. Understanding how the interactions and wiring of a multitude of individual nerve cells process and transmit this critical information to the brain is a fundamental goal in the field of neuroscience. One question many neuroscientists have tried to understand is how nerve cells in an animal’s brain detect direction when an animal sees movement of some kind – so-called motion vision. The raw signal from the light receptors in the eye does not discriminate whether the light moves in one direction or the other. So, the nerve cells in the brain must somehow compute the direction of movement based on the information relayed by the eye. For more than half a century, major debates have revolved around two rival models that could explain how motion vision works. Both models could in principle lead to neurons that prefer images moving in one direction over images moving in the opposite direction – so-called direction selectivity. In both models, the information about the changing light levels hitting two light-sensitive cells at two points on the eye are compared across time. In one model, signals from images moving in a cell’s preferred direction become amplified. In the other model, signals moving in the unfavored direction become canceled out. However, neither model perfectly explains motion vision. Now, Haag, Arenz et al. show that both models are partially correct and that the two mechanisms work together to detect motion across the field of vision more accurately. In the experiments, both models were tested in tiny fruit flies by measuring the activity of the first nerve cells that respond to the direction of visual motion. While each mechanism alone only produces a fairly weak and error-prone signal of direction, together the two mechanisms produce a stronger and more precise directional signal. Further research is now needed to determine which individual neurons amplify or cancel the signals to achieve such a high degree of direction selectivity. DOI: http://dx.doi.org/10.7554/eLife.17421.002

The optic lobe of Drosophila houses about 60,000 neurons that are organized in parallel, retinotopically arranged columns. Based on the Golgi-staining method, Fischbach and Dittrich ([1989] Cell Tissue Res 258:441–475) determined that each column contains about 90 identified cells. Each of these cells is supposed to release one or two different neurotransmitters. However, for most cells the released neurotransmitter is not known. Here we characterize the vast majority of the neurons in the Drosophila optic lobe that release acetylcholine (Ach), the major excitatory neurotransmitter of the insect central nervous system. We employed a promoter specific for cholinergic neurons and restricted its activity to single or a few cells using the MARCM technique. This approach allowed us to establish an anatomical map of neurons with a cholinergic phenotype based on their branching pattern. We identified 43 different types of neurons with a cholinergic phenotype. Thirty-one of them match previously described members of nine different subgroups: Transmedullary (Tm), Transmedullary Y (TmY), Medulla intrinsic (Mi, Mt, and Pm), Bushy T (T), Translobula Plate (Tlp), and Lobula intrinsic (Lcn and Lt) neurons (Fischbach and Dittrich [1989]). Intriguingly, 12 newly identified cell types suggest that previous Golgi studies were not saturating and that the actual number of different neurons per column is higher than previously thought. This study and similar ones on other neurotransmitter systems will contribute towards a columnar wiring diagram and foster the functional dissection of the visual circuitry in Drosophila. J. Comp. Neurol. 519:162-176, 2011. © 2010 Wiley-Liss, Inc.

Typically, neurons in sensory areas are highly interconnected. Coupling two neurons can synchronize their activity and affect a variety of single-cell properties, such as their stimulus tuning, firing rate or gain. All of these factors must be considered to understand how two neurons should be coupled to optimally process stimuli. We quantified the functional effect of an interaction between two optic-flow processing neurons (Vi and H1) in the fly (Lucilia sericata). Using a generative model, we estimated a uni-directional coupling from H1 to Vi. Especially at a low signal-to-noise ratio (SNR), the coupling strongly improved the information about optic-flow in Vi. We identified two constraints confining the strength of the interaction. First, for weak couplings, Vi benefited from inputs by H1 without a concomitant shift of its stimulus tuning. Second, at both low and high SNR, the coupling strength lay in a range in which the information carried by single spikes is optimal.

Motion vision provides essential cues for navigation and course control as well as for mate, prey, or predator detection. Consequently, neurons responding to visual motion in a direction-selective way are found in almost all species that see. However, directional information is not explicitly encoded at the level of a single photoreceptor. Rather, it has to be computed from the spatio-temporal excitation level of at least two photoreceptors. How this computation is done and how this computation is implemented in terms of neural circuitry and membrane biophysics have remained the focus of intense research over many decades. Here, we review recent progress made in this area with an emphasis on insects and the vertebrate retina.

SummaryRecent experiments have shown that motion detection in Drosophila starts with splitting the visual input into two parallel channels encoding brightness increments (ON) or decrements (OFF). This suggests the existence of either two (ON-ON, OFF-OFF) or four (for all pairwise interactions) separate motion detectors. To decide between these possibilities, we stimulated flies using sequences of ON and OFF brightness pulses while recording from motion-sensitive tangential cells. We found direction-selective responses to sequences of same sign (ON-ON, OFF-OFF), but not of opposite sign (ON-OFF, OFF-ON), refuting the existence of four separate detectors. Based on further measurements, we propose a model that reproduces a variety of additional experimental data sets, including ones that were previously interpreted as support for four separate detectors. Our experiments and the derived model mark an important step in guiding further dissection of the fly motion detection circuit.

Summary Moving animals experience constant sensory feedback, such as panoramic image shifts on the retina, termed optic flow. Underlying neuronal signals are thought to be important for exploratory behavior by signaling unintended course deviations and by providing spatial information about the environment [ 1 , 2 ]. Particularly in insects, the encoding of self-motion-related optic flow is well understood [ 1 , 2 , 3 , 4 , 5 ]. However, a gap remains in understanding how the associated neuronal activity controls locomotor trajectories. In flies, visual projection neurons belonging to two groups encode panoramic horizontal motion: horizontal system (HS) cells respond with depolarization to front-to-back motion and hyperpolarization to the opposite direction [ 6 , 7 ], and other neurons have the mirror-symmetrical response profile [ 6 , 8 , 9 ]. With primarily monocular sensitivity, the neurons’ responses are ambiguous for different rotational and translational self-movement components. Such ambiguities can be greatly reduced by combining signals from both eyes [ 10 , 11 , 12 ] to determine turning and movement speed [ 13 , 14 , 15 , 16 ]. Here, we explore the underlying functional logic by optogenetic HS cell manipulation in tethered walking Drosophila. We show that de- and hyperpolarization evoke opposite turning behavior, indicating that both direction-selective signals are transmitted to descending pathways for course control. Further experiments reveal a negative effect of bilaterally symmetric de- and hyperpolarization on walking velocity. Our results are therefore consistent with a functional architecture in which the HS cells’ membrane potential influences walking behavior bi-directionally via two decelerating pathways.

SUMMARY A central goal in sensory neuroscience is to fully characterize a neuron’s input-output relation. However, strong nonlinearities in the responses of sensory neurons have made it difficult to develop models that generalize to arbitrary stimuli. Typically, the standard linear-nonlinear models break down when neurons exhibit stimulus-dependent modulations of their gain or selectivity. We studied these issues in optic-flow processing neurons in the fly. We found that the neurons’ receptive fields are fully described by a time-varying vector field that is space-time separable. Increasing the stimulus strength, however, strongly reduces the neurons’ gain and selectivity. To capture these changes in response behavior, we extended the linear-nonlinear model by a biophysically motivated gain and selectivity mechanism. We fit all model parameters directly to the data and show that the model now characterizes the neurons’ input-output relation well over the full range of motion stimuli.

Many animals rely on vision to detect, locate, and track moving objects. In Drosophila courtship, males primarily use visual cues to orient toward and follow females and to select the ipsilateral wing for courtship song. Here, we show that the LC10 visual projection neurons convey essential visual information during courtship. Males with LC10 neurons silenced are unable to orient toward or maintain proximity to the female and do not predominantly use the ipsilateral wing when singing. LC10 neurons preferentially respond to small moving objects using an antagonistic motion-based center-surround mechanism. Unilateral activation of LC10 neurons recapitulates the orienting and ipsilateral wing extension normally elicited by females, and the potency with which LC10 induces wing extension is enhanced in a state of courtship arousal controlled by male-specific P1 neurons. These data suggest that LC10 is a major pathway relaying visual input to the courtship circuits in the male brain.

In the visual system of Drosophila, photoreceptors R1-R6 relay achromatic brightness information to five parallel pathways. Two of them, the lamina monopolar cells L1 and L2, represent the major input lines to the motion detection circuitry. We devised a new method for optical recording of visually evoked changes in intracellular Ca2+ in neurons using targeted expression of a genetically encoded Ca2+ indicator. Ca2+ in single terminals of L2 neurons in the medulla carried no information about the direction of motion. However, we found that brightness decrements (light-OFF) induced a strong increase in intracellular Ca2+ but brightness increments (light-ON) induced only small changes, suggesting that half-wave rectification of the input signal occurs. Thus, L2 predominantly transmits brightness decrements to downstream circuits that then compute the direction of image motion.

Fly motion vision and resultant compensatory optomotor responses are a classic example for neural computation. Here we review our current understanding of processing of optic flow as generated by an animal's self-motion. Optic flow processing is accomplished in a series of steps: First, the time-varying photoreceptor signals are fed into a two-dimensional array of Reichardt-type elementary motion detectors (EMDs). EMDs compute, in parallel, local motion vectors at each sampling point in space. Second, the output signals of many EMDs are spatially integrated on the dendrites of large-field tangential cells in the lobula plate. In the third step, tangential cells form extensive interactions with each other, giving rise to their large and complex receptive fields. Thus, tangential cells can act as matched filters tuned to optic flow during particular flight maneuvers. They finally distribute their information onto postsynaptic descending neurons, which either instruct the motor centers of the thoracic ganglion for flight and locomotion control or act themselves as motor neurons that control neck muscles for head movements.

In many species, motion-sensitive neurons responding to optic flow at higher processing stages are well characterized; however, less is known how this representation of ego-motion is further transformed into an appropriate motor response. Here, we analyzed in the blowflyCalliphora vicinathe visuomotor transformation from motion-sensitive neurons in the lobula plate [V2 and vertical system (VS) cells] onto premotor descending neurons [descending neurons of the ocellar and vertical system (DNOVS) cells] feeding into the motor circuit of the fly thoracic ganglion. We found that each of these cells is tuned to rotation of the fly around a particular body axis. Comparing the responses of presynaptic and postsynaptic cells revealed that DNOVS cells have approximately the same tuning widths as V2 and VS cells. However, DNOVS signals cells are less corrupted by fluctuations arising from the spatial structure of the visual input than their presynaptic elements. This leads to a more robust representation of ego-motion at the level of descending neurons. Thus, when moving from lobula plate cells to descending neurons, the selectivity for a particular optic flow remains unaltered, but the robustness of the representation increases.

In the visual system of the blowfly Calliphora vicina, neurons of the vertical system (VS cells) integrate wide-field motion information from a retinotopic array of local motion detectors. In vivo calcium imaging reveals two distinct and separate receptive fields in these cells: a narrow dendritic receptive field corresponding to feedforward input from the local motion detectors and a broad axon terminal receptive field that additionally incorporates input from neighboring cells mediated by lateral axo-axonal gap junctions. We show that the axon terminal responses are linear interpolations of the dendritic responses, resulting in a robust population coding of optic flow parameters as predicted by previous modeling studies. Compartmental modeling shows that spatially separating the axonal gap junctions from the conductive load of the dendritic synapses increases the coupling strength of the gap junctions, making this interpolation possible.

The nervous system of seeing animals derives information about optic flow in two subsequent steps. First, local motion vectors are calculated from moving retinal images, and second, the spatial distribution of these vectors is analyzed on the dendrites of large downstream neurons. In dipteran flies, this second step relies on a set of motion-sensitive lobula plate tangential cells (LPTCs), which have been studied in great detail in large fly species. Yet, studies on neurons that convey information to LPTCs and neuroanatomical investigations that enable a mechanistic understanding of the underlying dendritic computations in LPTCs are rare. We investigated the subcellular distribution of nicotinic acetylcholine receptors (nAChRs) on two sets of LPTCs: vertical system (VS) and horizontal system (HS) cells in Drosophila melanogaster. In this paper, we describe that both cell types express Dalpha7-type nAChR subunits specifically on higher order dendritic branches, similar to the expression of gamma aminobutyric acid (GABA) receptors. These findings support a model in which directional selectivity of LPTCs is achieved by the dendritic integration of excitatory, cholinergic, and inhibitory GABA-ergic input from local motion detectors with opposite preferred direction. Nonetheless, whole-cell recordings in mutant flies without Dalpha7 nAChRs revealed that direction selectivity of VS and HS cells is largely retained. In addition, mutant LPTCs were responsive to acetylcholine and remaining nAChR receptors were labeled by alpha-bungarotoxin. These results in LPTCs with genetically manipulated excitatory input synapses suggest a robust cellular implementation of dendritic processing that warrants direction selectivity. The underlying mechanism that ensures appropriate nAChR-mediated synaptic currents and the functional implications of separate sets or heteromultimeric nAChRs can now be addressed in this system.

SummaryWithin the last 400 million years, insects have radiated into at least a million species, accounting for more than half of all known living organisms: they are the most successful group in the animal kingdom, found in almost all environments of the planet, ranging in body size from a mere 0.1 mm up to half a meter. Their eyes, together with the respective parts of the nervous system dedicated to the processing of visual information, have long been the subject of intense investigation but, with the exception of some very basic reflexes, it is still not possible to link an insect's visual input to its behavioral output. Fortunately for the field, the fruit fly Drosophila is an insect, too. This genetic workhorse holds great promise for the insect vision field, offering the possibility of recording, suppressing or stimulating any single neuron in its nervous system. Here, I shall give a brief synopsis of what we currently know about insect vision, describe the genetic toolset available in Drosophila and give some recent examples of how the application of these tools have furthered our understanding of color and motion vision in Drosophila.

Many motion-sensitive tangential cells of the lobula plate in blowflies are well described with respect to their visual response properties and the connectivity among them. In addition to extensive connections between tangential cells within the lobula plate of one brain hemisphere, there exist many connections between the two hemispheres. Most of these connections have been found for neurons sensitive to horizontal motion. For neurons sensitive to vertical motion, however, only the connection of vertical sensitive cells (VS cells) and a cell (V1 cell) projecting to the other hemisphere has been demonstrated thus far. The ability to identify the presynaptic and postsynaptic cells as well as the good accessibility has made this specific synapse a model for graded transmission of synapses. However, the exact type of synapse, electrical or chemical, is not known. Investigating the connectivity between VS cells 1–3 and the V1 cell by means of dual recordings, we find that the VS cells are coupled via electrical synapses to the V1 cell. The results were confirmed by visualizing dye coupling between VS cells and V1.

SummaryThe crystalline-like structure of the optic lobes of the fruit fly Drosophila melanogaster has made them a model system for the study of neuronal cell-fate determination, axonal path finding, and target selection. For functional studies, however, the small size of the constituting visual interneurons has so far presented a formidable barrier. We have overcome this problem by establishing in vivo whole-cell recordings [1] from genetically targeted visual interneurons of Drosophila. Here, we describe the response properties of six motion-sensitive large-field neurons in the lobula plate that form a network consisting of individually identifiable, directionally selective cells most sensitive to vertical image motion (VS cells [2, 3]). Individual VS cell responses to visual motion stimuli exhibit all the characteristics that are indicative of presynaptic input from elementary motion detectors of the correlation type [4, 5]. Different VS cells possess distinct receptive fields that are arranged sequentially along the eye's azimuth, corresponding to their characteristic cellular morphology and position within the retinotopically organized lobula plate. In addition, lateral connections between individual VS cells cause strongly overlapping receptive fields that are wider than expected from their dendritic input. Our results suggest that motion vision in different dipteran fly species is accomplished in similar circuitries and according to common algorithmic rules. The underlying neural mechanisms of population coding within the VS cell network and of elementary motion detection, respectively, can now be analyzed by the combination of electrophysiology and genetic intervention in Drosophila.

Neurons in the nervous system can change their functional properties over time. At present, there are no techniques that allow reliable monitoring of changes within identified neurons over repeated experimental sessions. We increased the signal strength of troponin C-based calcium biosensors in the low-calcium regime by mutagenesis and domain rearrangement within the troponin C calcium binding moiety to generate the indicator TN-XXL. Using in vivo two-photon ratiometric imaging, we show that TN-XXL exhibits enhanced fluorescence changes in neurons of flies and mice. TN-XXL could be used to obtain tuning curves of orientation-selective neurons in mouse visual cortex measured repeatedly over days and weeks. Thus, the genetically encoded calcium indicator TN-XXL allows repeated imaging of response properties from individual, identified neurons in vivo, which will be crucial for gaining new insights into cellular mechanisms of plasticity, regeneration and disease.

In this work, we studied the adaptation of H1, a motion-sensitive neuron in the fly visual system, to the variance of randomly fluctuating velocity stimuli. We ask two questions. 1) Which components of the motion detection system undergo genuine adaptational changes in response to the variance of the fluctuating velocity signal? 2) What are the consequences of this adaptation for the information processing capabilities of the neuron? To address these questions, we characterized the adaptation of H1 by estimating the changes in the parameters of an associated Reichardt motion detection model under various stimulus conditions. The strongest stimulus dependence was exhibited by the temporal kernel of the motion detector and was parametrized by changes in the model's high-pass time constant (τH). This time constant shortened considerably with increasing velocity fluctuations. We showed that this adaptive process contributes significantly to the shortening of the velocity response time-course but not to velocity gain control. To assess the contribution of time-constant adaptation to information transmission, we compared the information rates generated by our adaptive model motion detector with model simulations in which τH was held fixed at its unadapted value for all stimulus conditions. We found that for intermediate stimulus conditions, fixing τH at its unadapted value led to higher information rates, suggesting that time-constant adaptation does not optimize total information rates about velocity trajectories. We also found that, over the wide range of stimulus conditions tested here, H1 information rates are dependent on the amplitude of velocity fluctuations.

Visual motion contains a wealth of information about self-motion as well as the three-dimensional structure of the environment. Therefore, it is of utmost importance for any organism with eyes. However, visual motion information is not explicitly represented at the photoreceptor level, but rather has to be computed by the nervous system from the changing retinal images as one of the first processing steps. Two prominent models have been proposed to account for this neural computation: the Reichardt detector and the gradient detector. While the Reichardt detector correlates the luminance levels derived from two adjacent image points, the gradient detector provides an estimate of the local retinal image velocity by dividing the spatial and the temporal luminance gradient. As a consequence of their different internal processing structure, both the models differ in a number of functional aspects such as their dependence on the spatial-pattern structure as well as their sensitivity to photon noise. These different properties lead to the proposal that an ideal motion detector should be of Reichardt type at low luminance levels, but of gradient type at high luminance levels. However, experiments on the fly visual systems provided unambiguous evidence in favour of the Reichardt detector under all luminance conditions. Does this mean that the fly nervous system uses suboptimal computations, or is there a functional aspect missing in the optimality criterion? In the following, I will argue in favour of the latter, showing that Reichardt detectors have an automatic gain control allowing them to dynamically adjust their input–output relationships to the statistical range of velocities presented, while gradient detectors do not have this property. As a consequence, Reichardt detectors, but not gradient detectors, always provide a maximum amount of information about stimulus velocity over a large range of velocities. This important property might explain why Reichardt type of computations have been demonstrated to underlie the extraction of motion information in the fly visual system under all luminance levels.