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

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

Modulation and neural correlates of postmating sleep plasticity in Drosophila females

Sleep is essential, but animals may forgo sleep to engage in other critical behaviors, such as feeding and reproduction. Previous studies have shown that female flies exhibit decreased sleep after mating, but our understanding of the process is limited. Here, we report that postmating nighttime sleep loss is modulated by diet and sleep deprivation, demonstrating a complex interaction among sleep, reproduction, and diet. We also find that female-specific pC1 neurons and sleep-promoting dorsal fan-shaped body (dFB) neurons are required for postmating sleep plasticity. Activating pC1 neurons leads to sleep suppression on standard fly culture media but has little sleep effect on sucrose-only food. Published connectome data suggest indirect, inhibitory connections among pC1 subtypes. Using calcium imaging, we show that activating the pC1e subtype inhibits dFB neurons. We propose that pC1 and dFB neurons integrate the mating status, food context, and sleep drive to modulate postmating sleep plasticity.

Neural Networks for Navigation: From Connections to Computations

Many animals can navigate toward a goal they cannot see based on an internal representation of that goal in the brain's spatial maps. These maps are organized around networks with stable fixed-point dynamics (attractors), anchored to landmarks, and reciprocally connected to motor control. This review summarizes recent progress in understanding these networks, focusing on studies in arthropods. One factor driving recent progress is the availability of the Drosophila connectome; however, it is increasingly clear that navigation depends on ongoing synaptic plasticity in these networks. Functional synapses appear to be continually reselected from the set of anatomical potential synapses based on the interaction of Hebbian learning rules, sensory feedback, attractor dynamics, and neuromodulation. This can explain how the brain's maps of space are rapidly updated; it may also explain how the brain can initialize goals as stable fixed points for navigation.

Olfactory navigation in arthropods

Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources-such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures-antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.

In search of behavioral and brain processes involved in honey bee dance communication

Honey bees represent an iconic model animal for studying the underlying mechanisms affecting advanced sensory and cognitive abilities during communication among colony mates. After von Frisch discovered the functional value of the waggle dance, this complex motor pattern led ethologists and neuroscientists to study its neural mechanism, behavioral significance, and implications for a collective organization. Recent studies have revealed some of the mechanisms involved in this symbolic form of communication by using conventional behavioral and pharmacological assays, neurobiological studies, comprehensive molecular and connectome analyses, and computational models. This review summarizes several critical behavioral and brain processes and mechanisms involved in waggle dance communication. We focus on the role of neuromodulators in the dancer and the recruited follower, the interneurons and their related processing in the first mechano-processing, and the computational navigation centers of insect brains.

A model of cue integration as vector summation in the insect brain

Ball-rolling dung beetles are known to integrate multiple cues in order to facilitate their straight-line orientation behaviour. Recent work has suggested that orientation cues are integrated according to a vector sum, that is, compass cues are represented by vectors and summed to give a combined orientation estimate. Further, cue weight (vector magnitude) appears to be set according to cue reliability. This is consistent with the popular Bayesian view of cue integration: cues are integrated to reduce or minimize an agent's uncertainty about the external world. Integration of orientation cues is believed to occur at the input to the insect central complex. Here, we demonstrate that a model of the head direction circuit of the central complex, including plasticity in input synapses, can act as a substrate for cue integration as vector summation. Further, we show that cue influence is not necessarily driven by cue reliability. Finally, we present a dung beetle behavioural experiment which, in combination with simulation, strongly suggests that these beetles do not weight cues according to reliability. We suggest an alternative strategy whereby cues are weighted according to relative contrast, which can also explain previous results.

A Visual Pathway into Central Complex for High-Frequency Motion-Defined Bars in Drosophila

Relative motion breaks a camouflaged target from a same-textured background, thus eliciting discrimination of a motion-defined object. Ring (R) neurons are critical components in the Drosophila central complex, which has been implicated in multiple visually guided behaviors. Using two-photon calcium imaging with female flies, we demonstrated that a specific population of R neurons that innervate the superior domain of bulb neuropil, termed superior R neurons, encoded a motion-defined bar with high spatial frequency contents. Upstream superior tuberculo-bulbar (TuBu) neurons transmitted visual signals by releasing acetylcholine within synapses connected with superior R neurons. Blocking TuBu or R neurons impaired tracking performance of the bar, which reveals their importance in motion-defined feature encoding. Additionally, the presentation of a low spatial frequency luminance-defined bar evoked consistent excitation in R neurons of the superior bulb, whereas either excited or inhibited responses were evoked in the inferior bulb. The distinct properties of the responses to the two bar stimuli indicate there is a functional division between the bulb subdomains. Moreover, physiological and behavioral tests with restricted lines suggest that R4d neurons play a vital role in tracking motion-defined bars. We conclude that the central complex receives the motion-defined features via a visual pathway from superior TuBu to R neurons and might encode different visual features via distinct response patterns at the population level, thereby driving visually guided behaviors.SIGNIFICANCE STATEMENT Animals could discriminate a motion-defined object that is indistinguishable with a same-textured background until it moves, but little is known about the underlying neural mechanisms. In this study, we identified that R neurons and their upstream partners, TuBu neurons, innervating the superior bulb of Drosophila central brain are involved in the discrimination of high-frequency motion-defined bars. Our study provides new evidence that R neurons receive multiple visual inputs from distinct upstream neurons, indicating a population coding mechanism for the fly central brain to discriminate diverse visual features. These results build progress in unraveling neural substrates for visually guided behaviors.

Neuroscience: Fish and fly headed in the same direction

Using functional imaging and neural circuit reconstructions, a recent study reveals head direction neurons in the anterior hindbrain of zebrafish that resemble insect head-direction cells to a surprising degree.

The Drivers of Diversity: Integrated genetic and hormonal cues regulate neural diversity

Proper functioning of the nervous system relies not only on the generation of a vast repertoire of distinct neural cell types but also on the precise neural circuitry within them. How the generation of highly diverse neural populations is regulated during development remains a topic of interest. Landmark studies in Drosophila have identified the genetic and temporal cues regulating neural diversity and thus have provided valuable insights into our understanding of temporal patterning of the central nervous system. The development of the Drosophila central complex, which is mostly derived from type II neural stem cell (NSC) lineages, showcases how a small pool of NSCs can give rise to vast and distinct progeny. Similar to the human outer subventricular zone (OSVZ) neural progenitors, type II NSCs generate intermediate neural progenitors (INPs) to expand and diversify lineages that populate higher brain centers. Each type II NSC has a distinct spatial identity and timely regulated expression of many transcription factors and mRNA binding proteins. Additionally, INPs derived from them show differential expression of genes depending on their birth order. Together type II NSCs and INPs display a combinatorial temporal patterning that expands neural diversity of the central brain lineages. We cover advances in current understanding of type II NSC temporal patterning and discuss similarities and differences in temporal patterning mechanisms of various NSCs with a focus on how cell-intrinsic and extrinsic hormonal cues regulate temporal transitions in NSCs during larval development. Cell extrinsic ligands activate conserved signaling pathways and extrinsic hormonal cues act as a temporal switch that regulate temporal progression of the NSCs. We conclude by elaborating on how a progenitor's temporal code regulates the fate specification and identity of distinct neural types. At the end, we also discuss open questions in linking developmental cues to neural identity, circuits, and underlying behaviors in the adult fly.

Ring neurons in the Drosophila central complex act as a rheostat for sensory modulation of aging

Sensory perception modulates aging, yet we know little about how. An understanding of the neuronal mechanisms through which animals orchestrate biological responses to relevant sensory inputs would provide insight into the control systems that may be important for modulating lifespan. Here, we provide new awareness into how the perception of dead conspecifics, or death perception, which elicits behavioral and physiological effects in many different species, affects lifespan in the fruit fly, Drosophila melanogaster. Previous work demonstrated that cohousing Drosophila with dead conspecifics decreases fat stores, reduces starvation resistance, and accelerates aging in a manner that requires both sight and the serotonin receptor 5-HT2A. In this manuscript, we demonstrate that a discrete, 5-HT2A-expressing neural population in the ellipsoid body (EB) of the Drosophila central complex, identified as R2/R4 neurons, acts as a rheostat and plays an important role in transducing sensory information about the presence of dead individuals to modulate lifespan. Expression of the insulin-responsive transcription factor foxo in R2/R4 neurons and insulin-like peptides dilp3 and dilp5, but not dilp2, are required, with the latter likely altered in median neurosecretory cells (MNCs) after R2/R4 neuronal activation. These data generate new insights into the neural underpinnings of how perceptive events may impact aging and physiology across taxa.

The RNA-binding protein, Imp specifies olfactory navigation circuitry and behavior in Drosophila

Complex behaviors depend on the precise developmental specification of neuronal circuits, but the relationship between genetic prograssms for neural development, circuit structure, and behavioral output is often unclear. The central complex (CX) is a conserved sensory-motor integration center in insects that governs many higher order behaviors and largely derives from a small number of Type II neural stem cells. Here, we show that Imp, a conserved IGF-II mRNA-binding protein expressed in Type II neural stem cells, specifies components of CX olfactory navigation circuitry. We show: (1) that multiple components of olfactory navigation circuitry arise from Type II neural stem cells and manipulating Imp expression in Type II neural stem cells alters the number and morphology of many of these circuit elements, with the most potent effects on neurons targeting the ventral layers of the fan-shaped body. (2) Imp regulates the specification of Tachykinin expressing ventral fan-shaped body input neurons. (3) Imp in Type II neural stem cells alters the morphology of the CX neuropil structures. (4) Loss of Imp in Type II neural stem cells abolishes upwind orientation to attractive odor while leaving locomotion and odor-evoked regulation of movement intact. Taken together, our work establishes that a single temporally expressed gene can regulate the expression of a complex behavior through the developmental specification of multiple circuit components and provides a first step towards a developmental dissection of the CX and its roles in behavior.

Visual processing in the fly, from photoreceptors to behavior

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

retro-Tango enables versatile retrograde circuit tracing in Drosophila

Transsynaptic tracing methods are crucial tools in studying neural circuits. Although a couple of anterograde tracing methods and a targeted retrograde tool have been developed in Drosophila melanogaster, there is still need for an unbiased, user-friendly, and flexible retrograde tracing system. Here, we describe retro-Tango, a method for transsynaptic, retrograde circuit tracing and manipulation in Drosophila. In this genetically encoded system, a ligand-receptor interaction at the synapse triggers an intracellular signaling cascade that results in reporter gene expression in presynaptic neurons. Importantly, panneuronal expression of the elements of the cascade renders this method versatile, enabling its use not only to test hypotheses but also to generate them. We validate retro-Tango in various circuits and benchmark it by comparing our findings with the electron microscopy reconstruction of the Drosophila hemibrain. Our experiments establish retro-Tango as a key method for circuit tracing in neuroscience research.

The influence of stimulus history on directional coding in the monarch butterfly brain

The central complex is a brain region in the insect brain that houses a neural network specialized to encode directional information. Directional coding has traditionally been investigated with compass cues that revolve in full rotations and at constant angular velocities around the insect's head. However, these stimulus conditions do not fully simulate an insect's sensory perception of compass cues during navigation. In nature, an insect flight is characterized by abrupt changes in moving direction as well as constant changes in velocity. The influence of such varying cue dynamics on compass coding remains unclear. We performed long-term tetrode recordings from the brain of monarch butterflies to study how central complex neurons respond to different stimulus velocities and directions. As these butterflies derive directional information from the sun during migration, we measured the neural response to a virtual sun. The virtual sun was either presented as a spot that appeared at random angular positions or was rotated around the butterfly at different angular velocities and directions. By specifically manipulating the stimulus velocity and trajectory, we dissociated the influence of angular velocity and direction on compass coding. While the angular velocity substantially affected the tuning directedness, the stimulus trajectory influenced the shape of the angular tuning curve. Taken together, our results suggest that the central complex flexibly adjusts its directional coding to the current stimulus dynamics ensuring a precise compass even under highly demanding conditions such as during rapid flight maneuvers.

Parallel motion vision pathways in the brain of a tropical bee

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

Multisensory navigation and neuronal plasticity in desert ants

Cataglyphis desert ants are skilled visual navigators. Here, I present a brief overview of multisensory learning and neuronal plasticity in ants, with a particular focus on the transition from the dark nest interior to performing first foraging trips. This highlights desert ants as experimental models for studying neuronal mechanisms underlying behavioral development into successful navigators.

Lineages to circuits: the developmental and evolutionary architecture of information channels into the central complex

The representation and integration of internal and external cues is crucial for any organism to execute appropriate behaviors. In insects, a highly conserved region of the brain, the central complex (CX), functions in the representation of spatial information and behavioral states, as well as the transformation of this information into desired navigational commands. How does this relatively invariant structure enable the incorporation of information from the diversity of anatomical, behavioral, and ecological niches occupied by insects? Here, we examine the input channels to the CX in the context of their development and evolution. Insect brains develop from ~ 100 neuroblasts per hemisphere that divide systematically to form "lineages" of sister neurons, that project to their target neuropils along anatomically characteristic tracts. Overlaying this developmental tract information onto the recently generated Drosophila "hemibrain" connectome and integrating this information with the anatomical and physiological recording of neurons in other species, we observe neuropil and lineage-specific innervation, connectivity, and activity profiles in CX input channels. We posit that the proliferative potential of neuroblasts and the lineage-based architecture of information channels enable the modification of neural networks across existing, novel, and deprecated modalities in a species-specific manner, thus forming the substrate for the evolution and diversification of insect navigational circuits.

Visual learning in tethered bees modifies flight orientation and is impaired by epinastine

Visual-orientation learning of a tethered flying bee was investigated using a flight simulator and a novel protocol in which orientation preference toward trained visual targets was assessed in tests performed before and after appetitive conditioning. Either a blue or a green rectangle (conditioned stimulus, CS) was associated with 30% sucrose solution (unconditioned stimulus, US), whereas the other rectangle was not paired with US. Bees were tested in a closed-looped flight simulator 5 min after ten pairings of the US and CS. Conditioned bees were preferentially oriented to the CS after such training. This increase in preference for CS was maintained for 24 h, indicating the presence of long-term memory. Because the total orienting time was not altered by conditioning, conditioning did not enhance orientation activity itself but increased the relative time for orientation to CS. When 0.4 or 4 mM epinastine (an antagonist of octopamine receptors) was injected into the bee's head 30 min prior to the experiment, both short- and long-term memory formation were significantly impaired, suggesting that octopamine, which is crucial for appetitive olfactory learning in insects, is also involved in visual orientation learning.

The connectome of an insect brain

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

Bayesian inference in ring attractor networks

Working memories are thought to be held in attractor networks in the brain. These attractors should keep track of the uncertainty associated with each memory, so as to weigh it properly against conflicting new evidence. However, conventional attractors do not represent uncertainty. Here, we show how uncertainty could be incorporated into an attractor, specifically a ring attractor that encodes head direction. First, we introduce a rigorous normative framework (the circular Kalman filter) for benchmarking the performance of a ring attractor under conditions of uncertainty. Next, we show that the recurrent connections within a conventional ring attractor can be retuned to match this benchmark. This allows the amplitude of network activity to grow in response to confirmatory evidence, while shrinking in response to poor-quality or strongly conflicting evidence. This "Bayesian ring attractor" performs near-optimal angular path integration and evidence accumulation. Indeed, we show that a Bayesian ring attractor is consistently more accurate than a conventional ring attractor. Moreover, near-optimal performance can be achieved without exact tuning of the network connections. Finally, we use large-scale connectome data to show that the network can achieve near-optimal performance even after we incorporate biological constraints. Our work demonstrates how attractors can implement a dynamic Bayesian inference algorithm in a biologically plausible manner, and it makes testable predictions with direct relevance to the head direction system as well as any neural system that tracks direction, orientation, or periodic rhythms.

Navigating Like a Fly: Drosophila melanogaster as a Model to Explore the Contribution of Serotonergic Neurotransmission to Spatial Navigation

Serotonin is a monoamine that acts in vertebrates and invertebrates as a modulator promoting changes in the structure and activity of brain areas relevant to animal behavior, ranging from sensory perception to learning and memory. Whether serotonin contributes in Drosophila to human-like cognitive abilities, including spatial navigation, is an issue little studied. Like in vertebrates, the serotonergic system in Drosophila is heterogeneous, meaning that distinct serotonergic neurons/circuits innervate specific fly brain regions to modulate precise behaviors. Here we review the literature that supports that serotonergic pathways modify different aspects underlying the formation of navigational memories in Drosophila.

Impact of central complex lesions on innate and learnt visual navigation in ants

Wood ants are excellent navigators, using a combination of innate and learnt navigational strategies to travel between their nest and feeding sites. Visual navigation in ants has been studied extensively, however, we have little direct evidence for the underlying neural mechanisms. Here, we perform lateralized mechanical lesions in the central complex (CX) of wood ants, a midline structure known to allow an insect to keep track of the direction of sensory cues relative to its own orientation and to control movement. We lesioned two groups of ants and observed their behaviour in an arena with a large visual landmark present. The first group of ants were naïve and when intact such ants show a clear innate attraction to the conspicuous landmark. The second group of ants were trained to aim to a food location to the side of the landmark. The general heading of naïve ants towards a visual cue was not altered by the lesions, but the heading of ants trained to a landmark adjacent food position was affected. Thus, CX lesions had a specific impact on learnt visual guidance. We also observed that lateralised lesions altered the fine details of turning with lesioned ants spending less time turning to the side ipsilateral of the lesion. The results confirm the role of the CX in turn control and highlight its important role in the implementation of learnt behaviours that rely on information from other brain regions.

Global inhibition in head-direction neural circuits: a systematic comparison between connectome-based spiking neural circuit models

The recent discovery of the head-direction (HD) system in fruit flies has provided unprecedented insights into the neural mechanisms of spatial orientation. Despite the progress, the neural substance of global inhibition, an essential component of the HD circuits, remains controversial. Some studies suggested that the ring neurons provide global inhibition, while others suggested the Δ7 neurons. In the present study, we provide evaluations from the theoretical perspective by performing systematic analyses on the computational models based on the ring-neuron (R models) and Δ7-neurons (Delta models) hypotheses with modifications according to the latest connectomic data. We conducted four tests: robustness, persistency, speed, and dynamical characteristics. We discovered that the two models led to a comparable performance in general, but each excelled in different tests. The R Models were more robust, while the Delta models were better in the persistency test. We also tested a hybrid model that combines both inhibitory mechanisms. While the performances of the R and Delta models in each test are highly parameter-dependent, the Hybrid model performed well in all tests with the same set of parameters. Our results suggest the possibility of combined inhibitory mechanisms in the HD circuits of fruit flies.

An intrinsic oscillator underlies visual navigation in ants

Many insects display lateral oscillations while moving, but how these oscillations are produced and participate in visual navigation remains unclear. Here, we show that visually navigating ants continuously display regular lateral oscillations coupled with variations of forward speed that strongly optimize the distance covered while simultaneously enabling them to scan left and right directions. This pattern of movement is produced endogenously and conserved across navigational contexts in two phylogenetically distant ant species. Moreover, the oscillations' amplitude can be modulated by both innate or learnt visual cues to adjust the exploration/exploitation balance to the current need. This lower-level motor pattern thus drastically reduces the degree of freedom needed for higher-level strategies to control behavior. The observed dynamical signature readily emerges from a simple neural circuit model of the insect's conserved pre-motor area known as the lateral accessory lobe, offering a surprisingly simple but effective neural control and endorsing oscillation as a core, ancestral way of moving in insects.

Subtype-Specific Roles of Ellipsoid Body Ring Neurons in Sleep Regulation in Drosophila

The ellipsoid body (EB) is a major structure of the central complex of the Drosophila melanogaster brain. Twenty-two subtypes of EB ring neurons have been identified based on anatomic and morphologic characteristics by light-level microscopy and EM connectomics. A few studies have associated ring neurons with the regulation of sleep homeostasis and structure. However, cell type-specific and population interactions in the regulation of sleep remain unclear. Using an unbiased thermogenetic screen of EB drivers using female flies, we found the following: (1) multiple ring neurons are involved in the modulation of amount of sleep and structure in a synergistic manner; (2) analysis of data for ΔP(doze)/ΔP(wake) using a mixed Gaussian model detected 5 clusters of GAL4 drivers which had similar effects on sleep pressure and/or depth: lines driving arousal contained R4m neurons, whereas lines that increased sleep pressure had R3m cells; (3) a GLM analysis correlating ring cell subtype and activity-dependent changes in sleep parameters across all lines identified several cell types significantly associated with specific sleep effects: R3p was daytime sleep-promoting, and R4m was nighttime wake-promoting; and (4) R3d cells present in 5HT7-GAL4 and in GAL4 lines, which exclusively affect sleep structure, were found to contribute to fragmentation of sleep during both day and night. Thus, multiple subtypes of ring neurons distinctively control sleep amount and/or structure. The unique highly interconnected structure of the EB suggests a local-network model worth future investigation; understanding EB subtype interactions may provide insight how sleep circuits in general are structured.SIGNIFICANCE STATEMENT How multiple brain regions, with many cell types, can coherently regulate sleep remains unclear, but identification of cell type-specific roles can generate opportunities for understanding the principles of integration and cooperation. The ellipsoid body (EB) of the fly brain exhibits a high level of connectivity and functional heterogeneity yet is able to tune multiple behaviors in real-time, including sleep. Leveraging the powerful genetic tools available in Drosophila and recent progress in the characterization of the morphology and connectivity of EB ring neurons, we identify several EB subtypes specifically associated with distinct aspects of sleep. Our findings will aid in revealing the rules of coding and integration in the brain.

The neuronal building blocks of the navigational toolkit in the central complex of insects

The central complex in the brain of insects is a group of midline-spanning neuropils at the interface between sensory and premotor tasks of the brain. It is involved in sleep control, decision-making and most prominently in goal-directed locomotion behaviors. The recently published connectome of the central complex of Drosophila melanogaster is a milestone in understanding the intricacies of the central-complex circuits and will provide inspiration for testable hypotheses for the coming years. Here, I provide a basic neuroanatomical description of the central complex of Drosophila and other species and discuss some recent advancements, some of which, such as the discovery of coordinate transformation through vector math, have been predicted from connectomics data.

Local shape descriptors for neuron segmentation

We present an auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of local shape descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a study comparing several existing methods across various specimen, imaging techniques, and resolutions, auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinity-based segmentation methods to be on par with the current state of the art for neuron segmentation (flood-filling networks), while being two orders of magnitudes more efficient-a critical requirement for the processing of future petabyte-sized datasets.

Emergent behaviour and neural dynamics in artificial agents tracking odour plumes

Tracking an odour plume to locate its source under variable wind and plume statistics is a complex task. Flying insects routinely accomplish such tracking, often over long distances, in pursuit of food or mates. Several aspects of this remarkable behaviour and its underlying neural circuitry have been studied experimentally. Here we take a complementary in silico approach to develop an integrated understanding of their behaviour and neural computations. Specifically, we train artificial recurrent neural network agents using deep reinforcement learning to locate the source of simulated odour plumes that mimic features of plumes in a turbulent flow. Interestingly, the agents' emergent behaviours resemble those of flying insects, and the recurrent neural networks learn to compute task-relevant variables with distinct dynamic structures in population activity. Our analyses put forward a testable behavioural hypothesis for tracking plumes in changing wind direction, and we provide key intuitions for memory requirements and neural dynamics in odour plume tracking.

Integration of optic flow into the sky compass network in the brain of the desert locust

Flexible orientation through any environment requires a sense of current relative heading that is updated based on self-motion. Global external cues originating from the sky or the earth's magnetic field and local cues provide a reference frame for the sense of direction. Locally, optic flow may inform about turning maneuvers, travel speed and covered distance. The central complex in the insect brain is associated with orientation behavior and largely acts as a navigation center. Visual information from global celestial cues and local landmarks are integrated in the central complex to form an internal representation of current heading. However, it is less clear how optic flow is integrated into the central-complex network. We recorded intracellularly from neurons in the locust central complex while presenting lateral grating patterns that simulated translational and rotational motion to identify these sites of integration. Certain types of central-complex neurons were sensitive to optic-flow stimulation independent of the type and direction of simulated motion. Columnar neurons innervating the noduli, paired central-complex substructures, were tuned to the direction of simulated horizontal turns. Modeling the connectivity of these neurons with a system of proposed compass neurons can account for rotation-direction specific shifts in the activity profile in the central complex corresponding to turn direction. Our model is similar but not identical to the mechanisms proposed for angular velocity integration in the navigation compass of the fly Drosophila.

Behavioral algorithms and neural mechanisms underlying odor-modulated locomotion in insects

Odors released from mates and resources such as a host and food are often the first sensory signals that an animal can detect. Changes in locomotion in response to odors are an important mechanism by which animals access resources important to their survival. Odor-modulated changes in locomotion in insects constitute a whole suite of flexible behaviors that allow insects to close in on these resources from long distances and perform local searches to locate and subsequently assess them. Here, we review changes in odor-mediated locomotion across many insect species. We emphasize that changes in locomotion induced by odors are diverse. In particular, the olfactory stimulus is sporadic at long distances and becomes more continuous at short distances. This distance-dependent change in temporal profile produces a corresponding change in an insect's locomotory strategy. We also discuss the neural circuits underlying odor modulation of locomotion.

The sky compass network in the brain of the desert locust

Many arthropods and vertebrates use celestial signals such as the position of the sun during the day or stars at night as compass cues for spatial orientation. The neural network underlying sky compass coding in the brain has been studied in great detail in the desert locust Schistocerca gregaria. These insects perform long-range migrations in Northern Africa and the Middle East following seasonal changes in rainfall. Highly specialized photoreceptors in a dorsal rim area of their compound eyes are sensitive to the polarization of the sky, generated by scattered sunlight. These signals are combined with direct information on the sun position in the optic lobe and anterior optic tubercle and converge from both eyes in a midline crossing brain structure, the central complex. Here, head direction coding is achieved by a compass-like arrangement of columns signaling solar azimuth through a 360° range of space by combining direct brightness cues from the sun with polarization cues matching the polarization pattern of the sky. Other directional cues derived from wind direction and internal self-rotation input are likely integrated. Signals are transmitted as coherent steering commands to descending neurons for directional control of locomotion and flight.

The role of learning-walk related multisensory experience in rewiring visual circuits in the desert ant brain

Efficient spatial orientation in the natural environment is crucial for the survival of most animal species. Cataglyphis desert ants possess excellent navigational skills. After far-ranging foraging excursions, the ants return to their inconspicuous nest entrance using celestial and panoramic cues. This review focuses on the question about how naïve ants acquire the necessary spatial information and adjust their visual compass systems. Naïve ants perform structured learning walks during their transition from the dark nest interior to foraging under bright sunlight. During initial learning walks, the ants perform rotational movements with nest-directed views using the earth’s magnetic field as an earthbound compass reference. Experimental manipulations demonstrate that specific sky compass cues trigger structural neuronal plasticity in visual circuits to integration centers in the central complex and mushroom bodies. During learning walks, rotation of the sky-polarization pattern is required for an increase in volume and synaptic complexes in both integration centers. In contrast, passive light exposure triggers light-spectrum (especially UV light) dependent changes in synaptic complexes upstream of the central complex. We discuss a multisensory circuit model in the ant brain for pathways mediating structural neuroplasticity at different levels following passive light exposure and multisensory experience during the performance of learning walks.

Dopamine promotes head direction plasticity during orienting movements

In neural networks that store information in their connection weights, there is a tradeoff between sensitivity and stability1,2. Connections must be plastic to incorporate new information, but if they are too plastic, stored information can be corrupted. A potential solution is to allow plasticity only during epochs when task-specific information is rich, on the basis of a 'when-to-learn' signal3. We reasoned that dopamine provides a when-to-learn signal that allows the brain's spatial maps to update when new spatial information is available-that is, when an animal is moving. Here we show that the dopamine neurons innervating the Drosophila head direction network are specifically active when the fly turns to change its head direction. Moreover, their activity scales with moment-to-moment fluctuations in rotational speed. Pairing dopamine release with a visual cue persistently strengthens the cue's influence on head direction cells. Conversely, inhibiting these dopamine neurons decreases the influence of the cue. This mechanism should accelerate learning during moments when orienting movements are providing a rich stream of head direction information, allowing learning rates to be low at other times to protect stored information. Our results show how spatial learning in the brain can be compressed into discrete epochs in which high learning rates are matched to high rates of information intake.

Connectomics and the neural basis of behaviour

Methods to acquire and process synaptic-resolution electron-microscopy datasets have progressed very rapidly, allowing production and annotation of larger, more complete connectomes. More accurate neuronal matching techniques are enriching cell type data with gene expression, neuron activity, behaviour and developmental information, providing ways to test hypotheses of circuit function. In a variety of behaviours such as learned and innate olfaction, navigation and sexual behaviour, connectomics has already revealed interconnected modules with a hierarchical structure, recurrence and integration of sensory streams. Comparing individual connectomes to determine which circuit features are robust and which are variable is one key research area; new work in comparative connectomics across development, experience, sex and species will establish strong links between neuronal connectivity and brain function.

Sleep need-dependent changes in functional connectivity facilitate transmission of homeostatic sleep drive

How the homeostatic drive for sleep accumulates over time and is released remains poorly understood. In Drosophila, we previously identified the R5 ellipsoid body (EB) neurons as putative sleep drive neurons1 and recently described a mechanism by which astrocytes signal to these cells to convey sleep need.2 Here, we examine the mechanisms acting downstream of the R5 neurons to promote sleep. EM connectome data demonstrate that R5 neurons project to EPG neurons.3 Broad thermogenetic activation of EPG neurons promotes sleep, whereas inhibiting these cells reduces homeostatic sleep rebound. Perforated patch-clamp recordings reveal that EPG neurons exhibit elevated spontaneous firing following sleep deprivation, which likely depends on an increase in extrinsic excitatory inputs. Our data suggest that cholinergic R5 neurons participate in the homeostatic regulation of sleep, and epistasis experiments indicate that the R5 neurons act upstream of EPG neurons to promote sleep. Finally, we show that the physical and functional connectivity between the R5 and EPG neurons increases with greater sleep need. Importantly, dual patch-clamp recordings demonstrate that activating R5 neurons induces cholinergic-dependent excitatory postsynaptic responses in EPG neurons. Moreover, sleep loss triggers an increase in the amplitude of these responses, as well as in the proportion of EPG neurons that respond. Together, our data support a model whereby sleep drive strengthens the functional connectivity between R5 and EPG neurons, triggering sleep when a sufficient number of EPG neurons are activated. This process could enable the proper timing of the accumulation and release of sleep drive.

Interneurons of fan-shaped body promote arousal in Drosophila

Sleep is required to maintain physiological functions and is widely conserved across species. To understand the sleep-regulatory mechanisms, sleep-regulating genes and neuronal circuits are studied in various animal species. In the sleep-regulatory neuronal circuits in Drosophila melanogaster, the dorsal fan-shaped body (dFB) is a major sleep-promoting region. However, other sleep-regulating neuronal circuits were not well identified. We recently found that arousal-promoting T1 dopamine neurons, interneurons of protocerebral bridge (PB) neurons, and PB neurons innervating the ventral part of the FB form a sleep-regulatory circuit, which we named "the PB-FB pathway". In the exploration of other sleep-regulatory circuits, we found that activation of FB interneurons, also known as pontine neurons, promoted arousal. We then found that FB interneurons had possible connections with the PB-FB pathway and dFB neurons. Ca2+ imaging revealed that FB interneurons received excitatory signals from the PB-FB pathway. We also demonstrated the possible role of FB interneurons to regulate dFB neurons. These results suggested the role of FB interneurons in sleep regulation.

3D-atlas of the brain of the cockroach Rhyparobia maderae

The Madeira cockroach Rhyparobia maderae is a nocturnal insect and a prominent model organism for the study of circadian rhythms. Its master circadian clock, controlling circadian locomotor activity and sleep-wake cycles, is located in the accessory medulla of the optic lobe. For a better understanding of brain regions controlled by the circadian clock and brain organization of this insect in general, we created a three-dimensional (3D) reconstruction of all neuropils of the cerebral ganglia based on anti-synapsin and anti-γ-aminobutyric acid immunolabeling of whole mount brains. Forty-nine major neuropils were identified and three-dimensionally reconstructed. Single-cell dye fills complement the data and provide evidence for distinct subdivisions of certain brain areas. Most neuropils defined in the fruit fly Drosophila melanogaster could be distinguished in the cockroach as well. However, some neuropils identified in the fruit fly do not exist as distinct entities in the cockroach while others are lacking in the fruit fly. In addition to neuropils, major fiber systems, tracts, and commissures were reconstructed and served as important landmarks separating brain areas. Being a nocturnal insect, R. maderae is an important new species to the growing collection of 3D insect brain atlases and only the second hemimetabolous insect, for which a detailed 3D brain atlas is available. This atlas will be highly valuable for an evolutionary comparison of insect brain organization and will greatly facilitate addressing brain areas that are supervised by the circadian clock.

A neural circuit for wind-guided olfactory navigation

To navigate towards a food source, animals frequently combine odor cues about source identity with wind direction cues about source location. Where and how these two cues are integrated to support navigation is unclear. Here we describe a pathway to the Drosophila fan-shaped body that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify fan-shaped body local neurons called h∆C that receive input from this odor pathway and a previously described wind pathway. We show that h∆C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h∆C neurons promotes navigation in a reproducible direction, and that h∆C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h∆C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the fan-shaped body to support goal-directed navigation.

Sensory neuroecology and multimodal evolution across the genus Drosophila

The neural basis and genetic mechanisms for sensory evolution are increasingly being explored in depth across many closely related members of the Drosophila genus. This has, in part, been achieved due to the immense efforts toward adapting gene-editing technologies for additional, non-model species. Studies targeting both peripheral sensory variations, as well as interspecies divergence in coding or neural connectivity, have generated numerous, tangible examples of how and where the evolution of sensory-driven animal behavior has occurred. Here, we review and discuss studies that each aim to identify the neurobiological and genetic components of sensory system evolution to provide a comparative overview of the types of functional variations observed across both perceptual input and behavioral output. In addition, we examined the roles neuroecology and neuroevolution play in speciation events, such as courtship and intraspecies communication, as well as those aspects related to behavioral divergence in host navigation or egg-laying preferences. Through the investigation of comparative, large-scale trends and correlations across diverse, yet closely related species within this highly ecologically variable genus of flies, we can begin to describe the underlying pressures, mechanisms, and constraints that have guided sensory and nervous system evolution within the natural environments of these organisms.

What is a cell type and how to define it?

Cell types are the basic functional units of an organism. Cell types exhibit diverse phenotypic properties at multiple levels, making them challenging to define, categorize, and understand. This review provides an overview of the basic principles of cell types rooted in evolution and development and discusses approaches to characterize and classify cell types and investigate how they contribute to the organism's function, using the mammalian brain as a primary example. I propose a roadmap toward a conceptual framework and knowledge base of cell types that will enable a deeper understanding of the dynamic changes of cellular function under healthy and diseased conditions.

Endocrine cybernetics: neuropeptides as molecular switches in behavioural decisions

Plasticity in animal behaviour relies on the ability to integrate external and internal cues from the changing environment and hence modulate activity in synaptic circuits of the brain. This context-dependent neuromodulation is largely based on non-synaptic signalling with neuropeptides. Here, we describe select peptidergic systems in the Drosophila brain that act at different levels of a hierarchy to modulate behaviour and associated physiology. These systems modulate circuits in brain regions, such as the central complex and the mushroom bodies, which supervise specific behaviours. At the top level of the hierarchy there are small numbers of large peptidergic neurons that arborize widely in multiple areas of the brain to orchestrate or modulate global activity in a state and context-dependent manner. At the bottom level local peptidergic neurons provide executive neuromodulation of sensory gain and intrinsically in restricted parts of specific neuronal circuits. The orchestrating neurons receive interoceptive signals that mediate energy and sleep homeostasis, metabolic state and circadian timing, as well as external cues that affect food search, aggression or mating. Some of these cues can be triggers of conflicting behaviours such as mating versus aggression, or sleep versus feeding, and peptidergic neurons participate in circuits, enabling behaviour choices and switches.

Weighting of Celestial and Terrestrial Cues in the Monarch Butterfly Central Complex

Monarch butterflies rely on external cues for orientation during their annual long-distance migration from Northern US and Canada to Central Mexico. These external cues can be celestial cues, such as the sun or polarized light, which are processed in a brain region termed the central complex (CX). Previous research typically focused on how individual simulated celestial cues are encoded in the butterfly's CX. However, in nature, the butterflies perceive several celestial cues at the same time and need to integrate them to effectively use the compound of all cues for orientation. In addition, a recent behavioral study revealed that monarch butterflies can rely on terrestrial cues, such as the panoramic skyline, for orientation and use them in combination with the sun to maintain a directed flight course. How the CX encodes a combination of celestial and terrestrial cues and how they are weighted in the butterfly's CX is still unknown. Here, we examined how input neurons of the CX, termed TL neurons, combine celestial and terrestrial information. While recording intracellularly from the neurons, we presented a sun stimulus and polarized light to the butterflies as well as a simulated sun and a panoramic scene simultaneously. Our results show that celestial cues are integrated linearly in these cells, while the combination of the sun and a panoramic skyline did not always follow a linear integration of action potential rates. Interestingly, while the sun and polarized light were invariantly weighted between individual neurons, the sun stimulus and panoramic skyline were dynamically weighted when both stimuli were simultaneously presented. Taken together, this dynamic weighting between celestial and terrestrial cues may allow the butterflies to flexibly set their cue preference during navigation.

---Connectomic analysis of the Drosophila lateral neuron clock cells reveals the synaptic basis of functional pacemaker classes

The circadian clock orchestrates daily changes in physiology and behavior to ensure internal temporal order and optimal timing across the day. In animals, a central brain clock coordinates circadian rhythms throughout the body and is characterized by a remarkable robustness that depends on synaptic connections between constituent neurons. The clock neuron network of Drosophila, which shares network motifs with clock networks in the mammalian brain yet is built of many fewer neurons, offers a powerful model for understanding the network properties of circadian timekeeping. Here, we report an assessment of synaptic connectivity within a clock network, focusing on the critical lateral neuron (LN) clock neuron classes within the Janelia hemibrain dataset. Our results reveal that previously identified anatomical and functional subclasses of LNs represent distinct connectomic types. Moreover, we identify a small number of non-clock cell subtypes representing highly synaptically coupled nodes within the clock neuron network. This suggests that neurons lacking molecular timekeeping likely play integral roles within the circadian timekeeping network. To our knowledge, this represents the first comprehensive connectomic analysis of a circadian neuronal network.

Most organisms on Earth possess an internal timekeeping system which ensures that bodily processes such as sleep, wakefulness or digestion take place at the right time. These precise daily rhythms are kept in check by a master clock in the brain. There, thousands of neurons – some of which carrying an internal ‘molecular clock’ – connect to each other through structures known as synapses. Exactly how the resulting network is organised to support circadian timekeeping remains unclear.

To explore this question, Shafer, Gutierrez et al. focused on fruit flies, as recent efforts have systematically mapped every neuron and synaptic connection in the brain of this model organism. Analysing available data from the hemibrain connectome project at Janelia revealed that that the neurons with the most important timekeeping roles were in fact forming the fewest synapses within the network. In addition, neurons without internal molecular clocks mediated strong synaptic connections between those that did, suggesting that ‘clockless’ cells still play an integral role in circadian timekeeping.

With this research, Shafer, Gutierrez et al. provide unexpected insights into the organisation of the master body clock. Better understanding the networks that underpin circadian rhythms will help to grasp how and why these are disrupted in obesity, depression and Alzheimer’s disease.

A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain

The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice and humans. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain circuits at this scale poses significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for modeling circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of a massive number of local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.

Myoinhibitory peptides in the central complex of the locust Schistocerca gregaria and colocalization with locustatachykinin-related peptides

The central complex in the brain of insects provides a neural network for sensorimotor processing that is essential for spatial navigation and locomotion and plays a role in sleep control. Studies on the neurochemical architecture of the central complex have been performed especially in the fruit fly Drosophila melangoaster and the desert locust, Schistocerca gregaria. In several insect species, myoinhibitory peptides (MIPs) are involved in circadian control and sleep-wake regulation. To identify neurons that might underlie these functions, we investigated the distribution of MIPs in the central complex of the locust. In silico transcript analysis suggests the presence of eight different MIPs in the desert locust. Through immunolabeling, we identified five systems of central-complex neurons that express MIP-like peptides. Two systems constitute columnar neurons of the protocerebral bridge and the lower division of the central body, while the other three systems are columnar neurons (two systems) and tangential neurons (one system) of the upper division of the central body. The innervation pattern and cell count of two systems of columnar neurons revealed the existence of 18 instead of 16 columns of the protocerebral bridge. Immunostaining of preparations containing intracellularly stained single cells allowed us to further specify subtypes of labeled columnar neurons. Double-label experiments showed that three systems of MIP-immunostained columnar neurons are also locustatachykinin-immunoreactive. No colocalization was found with serotonin immunostaining. The data provide novel insights into the architecture of the locust central complex and suggest that MIPs play a prominent role within the central-complex network.

The Role of Central Complex Neurons in Prey Detection and Tracking in the Freely Moving Praying Mantis (Tenodera sinensis)

Complex tasks like hunting moving prey in an unpredictable environment require high levels of motor and sensory integration. An animal needs to detect and track suitable prey objects, measure their distance and orientation relative to its own position, and finally produce the correct motor output to approach and capture the prey. In the insect brain, the central complex (CX) is one target area where integration is likely to take place. In this study, we performed extracellular multi-unit recordings on the CX of freely hunting praying mantises (Tenodera sinensis). Initially, we recorded the neural activity of freely moving mantises as they hunted live prey. The recordings showed activity in cells that either reflected the mantis's own movements or the actions of a prey individual, which the mantises focused on. In the latter case, the activity increased as the prey moved and decreased when it stopped. Interestingly, cells ignored the movement of the other prey than the one to which the mantis attended. To obtain quantitative data, we generated simulated prey targets presented on an LCD screen positioned below the clear floor of the arena. The simulated target oscillated back and forth at various angles and distances. We identified populations of cells whose activity patterns were strongly linked to the appearance, movement, and relative position of the virtual prey. We refer to these as sensory responses. We also found cells whose activity preceded orientation movement toward the prey. We call these motor responses. Some cells showed both sensory and motor properties. Stimulation through tetrodes in some of the preparations could also generate similar movements. These results suggest the crucial importance of the CX to prey-capture behavior in predatory insects like the praying mantis and, hence, further emphasize its role in behaviorally and ecologically relevant contexts.

A three-dimensional atlas of the honeybee central complex, associated neuropils and peptidergic layers of the central body

The central complex (CX) in the brain of insects is a highly conserved group of midline-spanning neuropils consisting of the upper and lower division of the central body, the protocerebral bridge, and the paired noduli. These neuropils are the substrate for a number of behaviors, most prominently goal-oriented locomotion. Honeybees have been a model organism for sky-compass orientation for more than 70 years, but there is still very limited knowledge about the structure and function of their CX. To advance and facilitate research on this brain area, we created a high-resolution three-dimensional atlas of the honeybee's CX and associated neuropils, including the posterior optic tubercles, the bulbs, and the anterior optic tubercles. To this end, we developed a modified version of the iterative shape averaging technique, which allowed us to achieve high volumetric accuracy of the neuropil models. For a finer definition of spatial locations within the central body, we defined layers based on immunostaining against the neuropeptides locustatachykinin, FMRFamide, gastrin/cholecystokinin, and allatostatin and included them into the atlas by elastic registration. Our honeybee CX atlas provides a platform for future neuroanatomical work.

Categorizing Visual Information in Subpopulations of Honeybee Mushroom Body Output Neurons

Multisensory integration plays a central role in perception, as all behaviors usually require the input of different sensory signals. For instance, for a foraging honeybee the association of a food source includes the combination of olfactory and visual cues to be categorized as a flower. Moreover, homing after successful foraging using celestial cues and the panoramic scenery may be dominated by visual cues. Hence, dependent on the context, one modality might be leading and influence the processing of other modalities. To unravel the complex neural mechanisms behind this process we studied honeybee mushroom body output neurons (MBON). MBONs represent the first processing level after olfactory-visual convergence in the honeybee brain. This was physiologically confirmed in our previous study by characterizing a subpopulation of multisensory MBONs. These neurons categorize incoming sensory inputs into olfactory, visual, and olfactory-visual information. However, in addition to multisensory units a prominent population of MBONs was sensitive to visual cues only. Therefore, we asked which visual features might be represented at this high-order integration level. Using extracellular, multi-unit recordings in combination with visual and olfactory stimulation, we separated MBONs with multisensory responses from purely visually driven MBONs. Further analysis revealed, for the first time, that visually driven MBONs of both groups encode detailed aspects within this individual modality, such as light intensity and light identity. Moreover, we show that these features are separated by different MBON subpopulations, for example by extracting information about brightness and wavelength. Most interestingly, the latter MBON population was tuned to separate UV-light from other light stimuli, which were only poorly differentiated from each other. A third MBON subpopulation was neither tuned to brightness nor to wavelength and encoded the general presence of light. Taken together, our results support the view that the mushroom body, a high-order sensory integration, learning and memory center in the insect brain, categorizes sensory information by separating different behaviorally relevant aspects of the multisensory scenery and that these categories are channeled into distinct MBON subpopulations.

Mechanisms of Variability Underlying Odor-Guided Locomotion

Changes in locomotion mediated by odors (odor-guided locomotion) are an important mechanism by which animals discover resources important to their survival. Odor-guided locomotion, like most other behaviors, is highly variable. Variability in behavior can arise at many nodes along the circuit that performs sensorimotor transformation. We review these sources of variability in the context of the Drosophila olfactory system. While these sources of variability are important, using a model for locomotion, we show that another important contributor to behavioral variability is the stochastic nature of decision-making during locomotion as well as the persistence of these decisions: Flies choose the speed and curvature stochastically from a distribution and locomote with the same speed and curvature for extended periods. This stochasticity in locomotion will result in variability in behavior even if there is no noise in sensorimotor transformation. Overall, the noise in sensorimotor transformation is amplified by mechanisms of locomotion making odor-guided locomotion in flies highly variable.