Flexible navigational computations in the Drosophila central complex

Ring-shaped odor coding in the antennal lobe of migratory locusts

The representation of odors in the locust antennal lobe with its >2,000 glomeruli has long remained a perplexing puzzle. We employed the CRISPR-Cas9 system to generate transgenic locusts expressing the genetically encoded calcium indicator GCaMP in olfactory sensory neurons. Using two-photon functional imaging, we mapped the spatial activation patterns representing a wide range of ecologically relevant odors across all six developmental stages. Our findings reveal a functionally ring-shaped organization of the antennal lobe composed of specific glomerular clusters. This configuration establishes an odor-specific chemotopic representation by encoding different chemical classes and ecologically distinct odors in the form of glomerular rings. The ring-shaped glomerular arrangement, which we confirm by selective targeting of OR70a-expressing sensory neurons, occurs throughout development, and the odor-coding pattern within the glomerular population is consistent across developmental stages. Mechanistically, this unconventional spatial olfactory code reflects the locust-specific and multiplexed glomerular innervation pattern of the antennal lobe.

Neuroethology: Decoding the waggle dance

A new study combining high-speed video recordings and computational modeling has revealed an overlooked feature of the famous honeybee waggle dance, yielding the first biologically plausible neural circuit model of how the information transmitted via the waggle dance could be assimilated by the follower bees.

The processing of proprioceptive signals in distributed networks: insights from insect motor control

The integration of sensory information is required to maintain body posture and to generate robust yet flexible locomotion through unpredictable environments. To anticipate required adaptations in limb posture and enable compensation of sudden perturbations, an animal's nervous system assembles external (exteroception) and internal (proprioception) cues. Coherent neuronal representations of the proprioceptive context of the body and the appendages arise from the concerted action of multiple sense organs monitoring body kinetics and kinematics. This multimodal proprioceptive information, together with exteroceptive signals and brain-derived descending motor commands, converges onto premotor networks - i.e. the local neuronal circuitry controlling motor output and movements - within the ventral nerve cord (VNC), the insect equivalent of the vertebrate spinal cord. This Review summarizes existing knowledge and recent advances in understanding how local premotor networks in the VNC use convergent information to generate contextually appropriate activity, focusing on the example of posture control. We compare the role and advantages of distributed sensory processing over dedicated neuronal pathways, and the challenges of multimodal integration in distributed networks. We discuss how the gain of distributed networks may be tuned to enable the behavioral repertoire of these systems, and argue that insect premotor networks might compensate for their limited neuronal population size by, in comparison to vertebrate networks, relying more heavily on the specificity of their connections. At a time in which connectomics and physiological recording techniques enable anatomical and functional circuit dissection at an unprecedented resolution, insect motor systems offer unique opportunities to identify the mechanisms underlying multimodal integration for flexible motor control.

Emergent spatial goals in an integrative model of the insect central complex

The insect central complex appears to encode and process spatial information through vector manipulation. Here, we draw on recent insights into circuit structure to fuse previous models of sensory-guided navigation, path integration and vector memory. Specifically, we propose that the allocentric encoding of location provided by path integration creates a spatially stable anchor for converging sensory signals that is relevant in multiple behavioural contexts. The allocentric reference frame given by path integration transforms a goal direction into a goal location and we demonstrate through modelling that it can enhance approach of a sensory target in noisy, cluttered environments or with temporally sparse stimuli. We further show the same circuit can improve performance in the more complex navigational task of route following. The model suggests specific functional roles for circuit elements of the central complex that helps explain their high preservation across insect species.

A single neuron in C. elegans orchestrates multiple motor outputs through parallel modes of transmission

Animals generate a wide range of highly coordinated motor outputs, which allows them to execute purposeful behaviors. Individual neurons in the circuits that generate behaviors have a remarkable capacity for flexibility as they exhibit multiple axonal projections, transmitter systems, and modes of neural activity. How these multi-functional properties of neurons enable the generation of adaptive behaviors remains unknown. Here, we show that the HSN neuron in C. elegans evokes multiple motor programs over different timescales to enable a suite of behavioral changes during egg laying. Using HSN activity perturbations and in vivo calcium imaging, we show that HSN acutely increases egg laying and locomotion while also biasing the animals toward low-speed dwelling behavior over minutes. The acute effects of HSN on egg laying and high-speed locomotion are mediated by separate sets of HSN transmitters and different HSN axonal compartments. The long-lasting effects on dwelling are mediated in part by HSN release of serotonin, which is taken up and re-released by NSM, another serotonergic neuron class that directly evokes dwelling. Our results show how the multi-functional properties of a single neuron allow it to induce a coordinated suite of behaviors and also reveal that neurons can borrow serotonin from one another to control behavior.

Stem cell-specific ecdysone signaling regulates the development and function of a Drosophila sleep homeostat

Complex behaviors arise from neural circuits that are assembled from diverse cell types. Sleep is a conserved and essential behavior, yet little is known regarding how the nervous system generates neuron types of the sleep-wake circuit. Here, we focus on the specification of Drosophila sleep-promoting neurons-long-field tangential input neurons that project to the dorsal layers of the fan-shaped body neuropil in the central complex (CX). We use lineage analysis and genetic birth dating to identify two bilateral Type II neural stem cells that generate these dorsal fan-shaped body (dFB) neurons. We show that adult dFB neurons express Ecdysone-induced protein E93, and loss of Ecdysone signaling or E93 in Type II NSCs results in the misspecification of the adult dFB neurons. Finally, we show that E93 knockdown in Type II NSCs affects adult sleep behavior. Our results provide insight into how extrinsic hormonal signaling acts on NSCs to generate neuronal diversity required for adult sleep behavior. These findings suggest that some adult sleep disorders might derive from defects in stem cell-specific temporal neurodevelopmental programs.

Neural representation of goal direction in the monarch butterfly brain

Neural processing of a desired moving direction requires the continuous comparison between the current heading and the goal direction. While the neural basis underlying the current heading is well-studied, the coding of the goal direction remains unclear in insects. Here, we used tetrode recordings in tethered flying monarch butterflies to unravel how a goal direction is represented in the insect brain. While recording, the butterflies maintained robust goal directions relative to a virtual sun. By resetting their goal directions, we found neurons whose spatial tuning was tightly linked to the goal directions. Importantly, their tuning was unaffected when the butterflies changed their heading after compass perturbations, showing that these neurons specifically encode the goal direction. Overall, we here discovered invertebrate goal-direction neurons that share functional similarities to goal-direction cells reported in mammals. Our results give insights into the evolutionarily conserved principles of goal-directed spatial orientation in animals.

Hierarchical Modular Structure of the Drosophila Connectome

The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem, we applied novel community detection methods to analyze the synapse-level reconstruction of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically, and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts.Significance Statement The Hemibrain is a partial connectome of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Analyzing the structure of a network of this size requires novel and efficient computational tools. We applied a new community detection method to automatically uncover the modular structure in the Hemibrain dataset by maximizing a generalized modularity measure. This allowed us to resolve the community structure of the fly hemibrain at a range of spatial scales revealing a hierarchical organization of the network, where larger-scale modules are composed of smaller-scale structures. The method also allowed us to identify subnetworks with distinct cell and connectivity structures, such as the layered structures in the fan-shaped body, and the modular organization of the superior neuropil. Thus, network analysis methods can be adopted to the connectomes being reconstructed using modern experimental methods to reveal the organization of the brain across scales. This supports the view that such connectomes will allow us to uncover the organizational structure of the brain, which can ultimately lead to a better understanding of its function.

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 single neuron in C. elegans orchestrates multiple motor outputs through parallel modes of transmission

Animals generate a wide range of highly coordinated motor outputs, which allows them to execute purposeful behaviors. Individual neuron classes in the circuits that generate behavior have a remarkable capacity for flexibility, as they exhibit multiple axonal projections, transmitter systems, and modes of neural activity. How these multi-functional properties of neurons enable the generation of highly coordinated behaviors remains unknown. Here we show that the HSN neuron in C. elegans evokes multiple motor programs over different timescales to enable a suite of behavioral changes during egg-laying. Using HSN activity perturbations and in vivo calcium imaging, we show that HSN acutely increases egg-laying and locomotion while also biasing the animals towards low-speed dwelling behavior over longer timescales. The acute effects of HSN on egg-laying and high-speed locomotion are mediated by separate sets of HSN transmitters and different HSN axonal projections. The long-lasting effects on dwelling are mediated by HSN release of serotonin that is taken up and re-released by NSM, another serotonergic neuron class that directly evokes dwelling. Our results show how the multi-functional properties of a single neuron allow it to induce a coordinated suite of behaviors and also reveal for the first time that neurons can borrow serotonin from one another to control behavior.

Modulation of aversive value coding in the vertebrate and invertebrate brain

Avoiding potentially dangerous situations is key for the survival of any organism. Throughout life, animals learn to avoid environments, stimuli or actions that can lead to bodily harm. While the neural bases for appetitive learning, evaluation and value-based decision-making have received much attention, recent studies have revealed more complex computations for aversive signals during learning and decision-making than previously thought. Furthermore, previous experience, internal state and systems level appetitive-aversive interactions seem crucial for learning specific aversive value signals and making appropriate choices. The emergence of novel methodologies (computation analysis coupled with large-scale neuronal recordings, neuronal manipulations at unprecedented resolution offered by genetics, viral strategies and connectomics) has helped to provide novel circuit-based models for aversive (and appetitive) valuation. In this review, we focus on recent vertebrate and invertebrate studies yielding strong evidence that aversive value information can be computed by a multitude of interacting brain regions, and that past experience can modulate future aversive learning and therefore influence value-based decisions.

An 'instinct for learning': the learning flights and walks of bees, wasps and ants from the 1850s to now

The learning flights and walks of bees, wasps and ants are precisely coordinated movements that enable insects to memorise the visual surroundings of their nest or other significant places such as foraging sites. These movements occur on the first few occasions that an insect leaves its nest. They are of special interest because their discovery in the middle of the 19th century provided perhaps the first evidence that insects can learn and are not solely governed by instinct. Here, we recount the history of research on learning flights from their discovery to the present day. The first studies were conducted by skilled naturalists and then, over the following 50 years, by neuroethologists examining the insects' learning behaviour in the context of experiments on insect navigation and its underlying neural mechanisms. The most important property of these movements is that insects repeatedly fixate their nest and look in other favoured directions, either in a preferred compass direction, such as North, or towards preferred objects close to the nest. Nest facing is accomplished through path integration. Memories of views along a favoured direction can later guide an insect's return to its nest. In some ant species, the favoured direction is adjusted to future foraging needs. These memories can then guide both the outward and homeward legs of a foraging trip. Current studies of central areas of the insect brain indicate what regions implement the behavioural manoeuvres underlying learning flights and the resulting visual memories.

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.

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.

Food memory circuits regulate eating and energy balance

In mammals, learning circuits play an essential role in energy balance by creating associations between sensory cues and the rewarding qualities of food. This process is altered by diet-induced obesity, but the causes and mechanisms are poorly understood. Here, we exploited the relative simplicity and wealth of knowledge about the D. melanogaster reinforcement learning network, the mushroom body, in order to study the relationship between the dietary environment, dopamine-induced plasticity, and food associations. We show flies that are fed a high-sugar diet cannot make associations between sensory cues and the rewarding properties of sugar. This deficit was caused by diet exposure, not fat accumulation, and specifically by lower dopamine-induced plasticity onto mushroom body output neurons (MBONs) during learning. Importantly, food memories dynamically tune the output of MBONs during eating, which instead remains fixed in sugar-diet animals. Interestingly, manipulating the activity of MBONs influenced eating and fat mass, depending on the diet. Altogether, this work advances our fundamental understanding of the mechanisms, causes, and consequences of the dietary environment on reinforcement learning and ingestive behavior.

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.

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.

Polarized light compass decoding

The brains of some insects can encode and decode polarization information and obtain heading angle information. Referring to the encoding ability of insects, exponential function encoding is designed to improve the stability of the polarized light compass artificial neural network. However, in the decoding process, only neurons with the largest activation degree are used for decoding (maximum value decoding), so the heading information contained in other neurons is not used. Therefore, average value decoding (AVD) and weighted AVD are proposed to use the heading information contained in multiple neurons to determine the heading. In addition, concerning the phenomenon of threshold activation of insect neurons, threshold value decoding (TVD) and weighted TVD are proposed, which can effectively eliminate the interference of neurons with low activation. Moreover, this paper proposes to improve the heading determination accuracy of the artificial neural network through pre-training. The simulation and experimental results show that the new, to the best of our knowledge, decoding methods and pre-training can effectively improve the heading determination accuracy of the artificial neural network.

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.

Active anemosensing hypothesis: how flying insects could estimate ambient wind direction through sensory integration and active movement

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction and direction of motion. Here, we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging manoeuvres characteristic of plume tracking animals’ trajectories.

Innate visual attraction in wood ants is a hardwired behavior seen across different motivational and ecological contexts

Ants are expert navigators combining innate and learnt navigational strategies. Whereas we know that the ants' feeding state segregates visual-navigational memories in ants navigating along a learnt route, it is an open question if the motivational state also affects the ants' innate visual preferences. Wood ant foragers show an innate attraction to conspicuous visual cues. These foragers inhabit cluttered woodland habitat and feed on honeydew from aphids on trees. Hence, the attraction to 'tree-like' objects might be an ecologically relevant behavior that is tailored to the wood ants' foraging ecology. Foragers from other ant species with different foraging ecologies show very different innate attractions. We investigated here the innate visual response of wood ant foragers with different motivational states, i.e., unfed or fed, as well as males that show no foraging activity. Our results show that ants from all three groups orient toward a prominent visual cue, i.e., this intrinsic visuomotor response is not context-dependent, but a hardwired behavior seen across different motivational and ecological contexts.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00040-022-00867-3.

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.