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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.

Internal representations are thought to support the generation of flexible, long-timescale behavioral patterns in both animals and artificial agents. Here, we present a novel conceptual framework for how Drosophila use their internal representation of head direction to maintain preferred headings in their surroundings, and how they learn to modify these preferences in the presence of selective thermal reinforcement. To develop the framework, we analyzed flies' behavior in a classical operant visual learning paradigm and found that they use stochastically generated fixations and directed turns to express their heading preferences. Symmetries in the visual scene used in the paradigm allowed us to expose how flies' probabilistic behavior in this setting is tethered to their head direction representation. We describe how flies' ability to quickly adapt their behavior to the rules of their environment may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in the structure of their circuits. Many of the mechanisms we outline may also be relevant for rapidly adaptive behavior driven by internal representations in other animals, including mammals.

Many animals rely on an internal heading representation when navigating in varied environments1-10. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body3,11,12. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features13-16; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity17-22, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.

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 theDrosophilaCX, 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.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain.

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

Neural representations of head direction have been discovered in many different species. A large body of theoretical work has proposed that the dynamics associated with these representations might be generated, maintained, and updated by recurrent network structures called ring attractors. Ring attractor models rely on specific assumptions about the structure of excitatory and inhibitory connectivity. These assumptions have been difficult to test directly. We therefore performed electron-microscopy-based circuit reconstruction and RNA profiling of identified cell types in the heading direction system of Drosophila melanogaster to directly examine excitatory and inhibitory synaptic connectivity, generating a dataset that should serve as a reference for future functional studies of the network. Consistent with several theoretical models, we identified network motifs that have been hypothesized to maintain the heading representation in darkness, update it when the animal turns, and tether it to visual cues. Genetically targeted two-photon calcium imaging and thermogenetic perturbation of the constituent neuron types during behavior provided additional support for these functional roles. However, we also discovered network motifs absent in current models, including a surprising degree of recurrence between arbors of different neurons with mixed pre- and post-synaptic specializations. Overall, our results confirm that the Drosophila heading direction network contains the core components of a ring attractor while also revealing unpredicted structural features that might enable the heading system to accurately track the animal9s heading with a small number of neurons.

Many animals exhibit morning and evening peaks of locomotor behavior. In Drosophila, two corresponding circadian neural oscillators - M (morning) cells and E (evening) cells - each exhibits a corresponding morning or evening neural activity peak. Yet we know little of the neural circuitry by which distinct circadian oscillators produce specific outputs to precisely control behavioral episodes. Here we show that Ring Neurons of the Ellipsoid Body (EB-RNs) display spontaneous morning and evening neural activity peaks in vivo: these peaks coincide with the bouts of locomotor activity and result from independent activation by M and E pacemakers. Further, M and E cells regulate EB-RNs via identified PPM3 dopaminergic neurons, which project to the EB and are normally co-active with EB-RNs. These in vivo findings establish the fundamental elements of a circadian neuronal output pathway: distinct circadian oscillators independently drive a common pre-motor center, through the agency of specific dopaminergic interneurons.

Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

A navigating animal’s sensory experience is shaped not just by its surroundings, but by its movements within them, which in turn are influenced by its past experiences. Studying the intertwined roles of sensation, experience and directed action in navigation has been made easier by the development of virtual reality (VR) environments for head-fixed animals, which allow for quantitative measurements of behavior in well-controlled sensory conditions. VR has long featured in studies ofDrosophila melanogaster, but these experiments have typically relied on one-dimensional (1D) VR, effectively allowing the fly to change only its heading in a visual scene, and not its position. Here we explore how flies navigate in a two-dimensional (2D) visual VR environment that more closely resembles their experience during free behavior. We show that flies’ interaction with landmarks in 2D environments cannot be automatically derived from their behavior in simpler 1D environments. Using a novel paradigm, we then demonstrate that flies in 2D VR adapt their behavior in a visual environment in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies respond to optogenetic activation of sugar-sensing neurons by initiating a local search behavior. Finally, by pairing optogenetic activation of heat-sensing cells to the flies’ presence near visual landmarks of specific shapes, we elicit selective learned avoidance of landmarks associated with aversive “virtual heat”. These head-fixed paradigms set the stage for an interrogation of fly brain circuitry underlying flexible navigation in complex visual environments.

Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics, and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and tracking large populations of neurons using 2-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.

Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed Drosophila melanogaster walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body, a toroidal structure in the centre of the fly brain. The neural population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity, a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors, network structures that have been proposed to support the function of navigational brain circuits. Calcium imaging of the brain of tethered flies walking in a virtual reality arena showed that a population of neurons with dendrites that tile the ‘ellipsoid body’ use information from visual landmarks and the fly's own rotation to compute heading; this suggests insects possess neurons with similarities to ‘head direction cells’ known to contribute to spatial navigation in mammalian brains. How insect brains combine visual landmarks and path integration during navigation has been unknown. Johannes Seelig and Vivek Jayaraman perform calcium imaging of the brain of tethered flies walking in a virtual reality arena and show that a population of neurons with dendrites that tile the 'ellipsoid body' uses information from visual landmarks and the fly's own rotation to compute heading. This is the first evidence for an invertebrate equivalent of the 'head direction' neurons known to contribute to spatial navigation in mammalian brains.

Many animals maintain an internal representation of their heading as they move through their surroundings. Such a compass representation was recently discovered in a neural population in the Drosophila melanogaster central complex, a brain region implicated in spatial navigation. Here, we use two-photon calcium imaging and electrophysiology in head-fixed walking flies to identify a different neural population that conjunctively encodes heading and angular velocity, and is excited selectively by turns in either the clockwise or counterclockwise direction. We show how these mirror-symmetric turn responses combine with the neurons’ connectivity to the compass neurons to create an elegant mechanism for updating the fly’s heading representation when the animal turns in darkness. This mechanism, which employs recurrent loops with an angular shift, bears a resemblance to those proposed in theoretical models for rodent head direction cells. Our results provide a striking example of structure matching function for a broadly relevant computation. DOI: http://dx.doi.org/10.7554/eLife.23496.001

Summary Studying the intertwined roles of sensation, experience, and directed action in navigation has been facilitated by the development of virtual reality (VR) environments for head-fixed animals, allowing for quantitative measurements of behavior in well-controlled conditions. VR has long featured in studies of Drosophila melanogaster, but these experiments have typically allowed the fly to change only its heading in a visual scene and not its position. Here we explore how flies move in two dimensions (2D) using a visual VR environment that more closely captures an animal’s experience during free behavior. We show that flies’ 2D interaction with landmarks cannot be automatically derived from their orienting behavior under simpler one-dimensional (1D) conditions. Using novel paradigms, we then demonstrate that flies in 2D VR adapt their behavior in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies exploring a 2D VR respond to optogenetic activation of sugar-sensing neurons by initiating a local search, which appears not to rely on visual landmarks. Visual landmarks can, however, help flies to avoid areas in VR where they experience an aversive, optogenetically generated heat stimulus. By coupling aversive virtual heat to the flies’ presence near visual landmarks of specific shapes, we elicit selective learned avoidance of those landmarks. Thus, we demonstrate that head-fixed flies adaptively navigate in 2D virtual environments, but their reliance on visual landmarks is context dependent. These behavioral paradigms set the stage for interrogation of the fly brain circuitry underlying flexible navigation in complex multisensory environments.

Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultrasensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5-40-µm long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.

Hordes of tourists flock to Washington, D.C. every spring to see the cherry trees blossom. Once in the city, they must find their way to the Tidal Basin where the Japanese trees grow. Fortunately, a number of visual landmarks can help them to navigate. In 1910, the United States Congress passed The Height of Buildings Act, limiting the elevation of commercial and residential structures in D.C. to 130 feet. Thus, the 555-foot-tall Washington Monument often looms large against the horizon, serving as an anchor point to help set the tourists' sense of direction. Once their heading is set, they can lose sight of the monument behind buildings or groups of tall Scandinavian visitors and still use their internal compass to navigate to the Basin. This compass keeps track of their paces and turns and updates their sense of where they are and where they need to go. Yet while their heading informs their actions, it does not dictate them. Tourists who have been to D.C. in the past can, for example, use remembered views to alter their routes to avoid crowds. On an even finer scale, their leg movements also depend on their current state - they might increase the frequency and length of their strides if hunger pangs compete with their desire to see cherry blossoms, for example. The way in which these disparate cues and motivations influence exploration is a neuroscience mystery across creatures large and small.

Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging. DOI: http://dx.doi.org/10.7554/eLife.12727.001, eLife digest Neurons encode information with brief electrical pulses called spikes. Monitoring spikes in large populations of neurons is a powerful method for studying how networks of neurons process information and produce behavior. This activity can be detected using fluorescent protein indicators, or “probes”, which light up when neurons are active. The best existing probes produce green fluorescence. However, red fluorescent probes would allow us to see deeper into the brain, and could also be used with green probes to image the activity and interactions of different neuron types simultaneously. However, existing red fluorescent probes are not as good at detecting neural activity as green probes. By optimizing two existing red fluorescent proteins, Dana et al. have now produced two new red fluorescent probes, each with different advantages. The new protein indicators detect neural activity with high sensitivity and allow researchers to image previously unseen brain activity. Tests showed that the probes work in cultured neurons and allow imaging of the activity of neurons in mice, flies, fish and worms. History has shown that enhancing the techniques used to study biological processes can lead to fundamentally new insights. In the future, Dana et al. would therefore like to make even more sensitive protein indicators that will allow larger networks of neurons deeper in the brain to be imaged. DOI: http://dx.doi.org/10.7554/eLife.12727.002

Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Recent efforts in protein engineering have significantly increased the performance of GECIs. The state-of-the art single-wavelength GECI, GCaMP3, has been deployed in a number of model organisms and can reliably detect three or more action potentials in short bursts in several systemsin vivo. Through protein structure determination, targeted mutagenesis, high-throughput screening, and a battery ofin vitroassays, we have increased the dynamic range of GCaMP3 by severalfold, creating a family of “GCaMP5” sensors. We tested GCaMP5s in several systems: cultured neurons and astrocytes, mouse retina, andin vivoinCaenorhabditischemosensory neurons,Drosophilalarval neuromuscular junction and adult antennal lobe, zebrafish retina and tectum, and mouse visual cortex. Signal-to-noise ratio was improved by at least 2- to 3-fold. In the visual cortex, two GCaMP5 variants detected twice as many visual stimulus-responsive cells as GCaMP3. By combiningin vivoimaging with electrophysiology we show that GCaMP5 fluorescence provides a more reliable measure of neuronal activity than its predecessor GCaMP3. GCaMP5 allows more sensitive detection of neural activityin vivoand may find widespread applications for cellular imaging in general.

International audience; Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball's motion is tracked at high resolution and can be treated as a proxy for the fly's own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in horizontal-system neurons correlated with robust optomotor behavior during walking. Our technique allows both behavior and physiology in identified neurons to be monitored in a genetic model organism with an extensive repertoire of walking behaviors.

Genetically encoded calcium indicators (GECIs) can be used to image activity in defined neuronal populations. However, current GECIs produce inferior signals compared to synthetic indicators and recording electrodes, precluding detection of low firing rates. We developed a single-wavelength GCaMP2-based GECI (GCaMP3), with increased baseline fluorescence (3-fold), increased dynamic range (3-fold) and higher affinity for calcium (1.3-fold). We detected GCaMP3 fluorescence changes triggered by single action potentials in pyramidal cell dendrites, with signal-to-noise ratio and photostability substantially better than those of GCaMP2, D3cpVenus and TN-XXL. In Caenorhabditis elegans chemosensory neurons and the Drosophila melanogaster antennal lobe, sensory stimulation-evoked fluorescence responses were significantly enhanced with GCaMP3 (4-6-fold). In somatosensory and motor cortical neurons in the intact mouse, GCaMP3 detected calcium transients with amplitudes linearly dependent on action potential number. Long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.

Summary The visual neurons of many animals process sensory input differently depending on the animal's state of locomotion. Now, new work in Drosophila melanogaster shows that neuromodulatory neurons active during flight boost responses of neurons in the visual system.

Optogenetic tools enable examination of how specific cell types contribute to brain circuit functions. A long-standing question is whether it is possible to independently activate two distinct neural populations in mammalian brain tissue. Such a capability would enable the study of how different synapses or pathways interact to encode information in the brain. Here we describe two channelrhodopsins, Chronos and Chrimson, discovered through sequencing and physiological characterization of opsins from over 100 species of alga. Chrimson's excitation spectrum is red shifted by 45 nm relative to previous channelrhodopsins and can enable experiments in which red light is preferred. We show minimal visual system–mediated behavioral interference when using Chrimson in neurobehavioral studies in Drosophila melanogaster. Chronos has faster kinetics than previous channelrhodopsins yet is effectively more light sensitive. Together these two reagents enable two-color activation of neural spiking and downstream synaptic transmission in independent neural populations without detectable cross-talk in mouse brain slice. Postprint

Many animals, including insects, are known to use visual landmarks to orient in their environment. In Drosophila melanogaster, behavioural genetics studies have identified a higher brain structure called the central complex as being required for the fly's innate responses to vertical visual features and its short- and long-term memory for visual patterns. But whether and how neurons of the fly central complex represent visual features are unknown. Here we use two-photon calcium imaging in head-fixed walking and flying flies to probe visuomotor responses of ring neurons--a class of central complex neurons that have been implicated in landmark-driven spatial memory in walking flies and memory for visual patterns in tethered flying flies. We show that dendrites of ring neurons are visually responsive and arranged retinotopically. Ring neuron receptive fields comprise both excitatory and inhibitory subfields, resembling those of simple cells in the mammalian primary visual cortex. Ring neurons show strong and, in some cases, direction-selective orientation tuning, with a notable preference for vertically oriented features similar to those that evoke innate responses in flies. Visual responses were diminished during flight, but, in contrast with the hypothesized role of the central complex in the control of locomotion, not modulated during walking. Taken together, these results indicate that ring neurons represent behaviourally relevant visual features in the fly's environment, enabling downstream central complex circuits to produce appropriate motor commands. More broadly, this study opens the door to mechanistic investigations of circuit computations underlying visually guided action selection in the Drosophila central complex.

Drosophila melanogaster is a genetic model organism with many experimental advantages, including the ability to genetically manipulate specific sub-populations of neurons. The combination of physiology and genetic tools is increasingly being applied to questions in systems neuroscience [1].Our goal is to understand circuit computations underlying sensory-motor transformation in the fly brain. This requires recording not just neural activity but also the fly's behavior. Towards this end, we have developed a novel experimental setup [2] for two-photon calcium imaging while the fly is walking on an air-supported ‘Buchner’ ball [3, 4] in a virtual arena [5]. These recordings represent the first examples of functional imaging in behaving Drosophila and provide a platform for future explorations of decision-making and sensory-motor transformations in this powerful genetic model organism. We have also adapted the setup for calcium imaging in tethered flying Drosophila. In complementary work, a different group has succeeded in whole-cell patch-clamp recording from fruit flies during flight behavior [6].Motion-sensitive interneurons in the visual system of walking and flying Drosophila show modulation of their responses depending on their behavioral state [6, 7]. Under natural conditions the visual input of the fly changes and is controlled by the movement of the fly. Closed-loop tethered behavior allows approaching this situation in a controlled experimental setting. We demonstrated the feasibility of closed loop flight behavior during calcium imaging and compare neuronal responses during open and closed-loop flight behavior.1. Olsen and Wilson (Trends Neurosci., 2008)2. Seelig, Chiappe, Lott, Dutta, Osborne, Reiser, Jayaraman (Nat Meth, 2010)3. Gotz and Wenking (J Comp Physiol, 1973)4. Bohm, Schildberger and Huber (JEB, 1991)5. Reiser and Dickinson (J Neurosci Meth, 2008)6. Maimon, Straw, Dickinson (Nat Neurosci, 2010)7. Chiappe, Seelig, Reiser, Jayaraman, (Curr Biol, 2010)

SummaryChanges in behavioral state modify neural activity in many systems [1–5]. In some vertebrates such modulation has been observed and interpreted in the context of attention [2] and sensorimotor coordinate transformations [3]. Here we report state-dependent activity modulations during walking in a visual-motor pathway of Drosophila. We used two-photon imaging to monitor intracellular calcium activity in motion-sensitive lobula plate tangential cells (LPTCs) in head-fixed Drosophila walking on an air-supported ball. Cells of the horizontal system (HS)—a subgroup of LPTCs—showed stronger calcium transients in response to visual motion when flies were walking rather than resting. The amplified responses were also correlated with walking speed. Moreover, HS neurons showed a relatively higher gain in response strength at higher temporal frequencies, and their optimum temporal frequency was shifted toward higher motion speeds. Walking-dependent modulation of HS neurons in the Drosophila visual system may constitute a mechanism to facilitate processing of higher image speeds in behavioral contexts where these speeds of visual motion are relevant for course stabilization.

Nat. Methods 11, 338–346 (2014); published online 9 February 2014; corrected after print 28 August 2014 In the version of this article initially published, the Drosophila transgenic strains were incorrectly reported as generated using Chrimson (Fig. 3, Supplementary Figs. 14–16 and Supplementary Videos 2–6).

Corrigendum: Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior