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Many animals use an internal sense of direction to guide their movements through the world. Neurons selective to head direction are thought to support this directional sense and have been found in a diverse range of species, from insects to primates, highlighting their evolutionary importance. Across species, most head-direction networks share four key properties: a unique representation of direction at all times, persistent activity in the absence of movement, integration of angular velocity to update the representation, and the use of directional cues to correct drift. The dynamics of theorized network structures called ring attractors elegantly account for these properties, but their relationship to brain circuits is unclear. Here, we review experiments in rodents and flies that offer insights into potential neural implementations of ring attractor networks. We suggest that a theory-guided search across model systems for biological mechanisms that enable such dynamics would uncover general principles underlying head-direction circuit function.

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.

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 orient using visual cues, but how a single cue is selected from among many is poorly understood. Here we show that Drosophila ring neurons-central brain neurons implicated in navigation-display visual stimulus selection. Using in vivo two-color two-photon imaging with genetically encoded calcium indicators, we demonstrate that individual ring neurons inherit simple-cell-like receptive fields from their upstream partners. Stimuli in the contralateral visual field suppressed responses to ipsilateral stimuli in both populations. Suppression strength depended on when and where the contralateral stimulus was presented, an effect stronger in ring neurons than in their upstream inputs. This history-dependent effect on the temporal structure of visual responses, which was well modeled by a simple biphasic filter, may determine how visual references are selected for the fly's internal compass. Our approach highlights how two-color calcium imaging can help identify and localize the origins of sensory transformations across synaptically connected neural populations.

Representing direction in the fly A population of cells called compass neurons represents a fruitfly's heading direction. Kim et al. used imaging and optogenetics in behaving flies to elucidate the functional architecture of the underlying neuronal network. They observed local excitation and global inhibition between the compass neurons. The features of the network were best explained by a ring attractor network model. Until now, this hypothesized network structure has been difficult to demonstrate in a real brain. Science , this issue p. 849

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.

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.

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