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.

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.

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.

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.

A Neural Model for Insect Steering Applied to Olfaction and Path Integration.

Many animal behaviors require orientation and steering with respect to the environment. For insects, a key brain area involved in spatial orientation and navigation is the central complex. Activity in this neural circuit has been shown to track the insect's current heading relative to its environment and has also been proposed to be the substrate of path integration. However, it remains unclear how the output of the central complex is integrated into motor commands. Central complex output neurons project to the lateral accessory lobes (LAL), from which descending neurons project to thoracic motor centers. Here, we present a computational model of a simple neural network that has been described anatomically and physiologically in the LALs of male silkworm moths, in the context of odor-mediated steering. We present and analyze two versions of this network, one rate based and one based on spiking neurons. The modeled network consists of an inhibitory local interneuron and a bistable descending neuron (flip-flop) that both receive input in the LAL. The flip-flop neuron projects onto neck motor neurons to induce steering. We show that this simple computational model not only replicates the basic parameters of male silkworm moth behavior in a simulated odor plume but can also take input from a computational model of path integration in the central complex and use it to steer back to a point of origin. Furthermore, we find that increasing the level of detail within the model improves the realism of the model's behavior, leading to the emergence of looping behavior as an orientation strategy. Our results suggest that descending neurons originating in the LALs, such as flip-flop neurons, are sufficient to mediate multiple steering behaviors. This study is therefore a first step to close the gap between orientation circuits in the central complex and downstream motor centers.

Vector navigation in walking bumblebees.

Path integration is a computational strategy that allows an animal to maintain an internal estimate of its position relative to a point of origin. Many species use path integration to navigate back to specific locations, typically their homes, after lengthy and convoluted excursions. Hymenopteran insects are impressive path integrators, directly returning to their hives after hundreds of meters of outward travel. Recent neurobiological insights have established hypotheses for how path integration vectors could be encoded in the brains of bees, but clear ways to test these hypotheses in the laboratory are currently unavailable. Here, we report that the bumblebee, Bombus terrestris, uses path integration while walking over short distances in an indoor arena. They estimate accurate vector distances after displacement and orient by artificial celestial cues. Walking bumblebees also exhibited systematic search patterns when home vectors failed to lead them accurately back to the nest, closely resembling searches performed by other species under natural conditions. We thus provide a robust experimental system to test navigation behavior in the laboratory that reflects most aspects of natural path integration. Importantly, we established this assay in an animal that is both readily available and resilient to invasive manipulations, as we demonstrate with the retention of the homing behavior post-anesthesia and surgery. In the future, our behavioral assay can therefore be combined with current electrophysiological techniques, opening a path toward directly probing the neural basis of the sophisticated vector navigation abilities of bees.

Mapping the fly's 'brain in the brain'.

Studying neurons and their connections in the central complex of the fruit fly reveals new insights into how their structure and function shape perception and behavior.

Fly navigation: Yet another ring.

Flies keep track of a food site by path integration. A novel behavioral paradigm has been combined with computational models to show that Drosophila can track at least three food patches simultaneously by using the center of gravity of all food sites as the reference point for their path integrator.

A projectome of the bumblebee central complex.

Insects have evolved diverse and remarkable strategies for navigating in various ecologies all over the world. Regardless of species, insects share the presence of a group of morphologically conserved neuropils known collectively as the central complex (CX). The CX is a navigational center, involved in sensory integration and coordinated motor activity. Despite the fact that our understanding of navigational behavior comes predominantly from ants and bees, most of what we know about the underlying neural circuitry of such behavior comes from work in fruit flies. Here, we aim to close this gap, by providing the first comprehensive map of all major columnar neurons and their projection patterns in the CX of a bee. We find numerous components of the circuit that appear to be highly conserved between the fly and the bee, but also highlight several key differences which are likely to have important functional ramifications.

Bumblebees forage widely for pollen and nectar from flowers, sometimes travelling kilometers away from their nest, but they can somehow always find their way home in a nearly straight line. These insects have been known to return to their nest from new locations almost 10 kilometers away. This homing ability is a complex neurological feat and requires the brain to combine several processes, including observing the external world, controlling bodily movements and drawing on memory. While the navigational behavior of bees has been well-studied, the neuronal circuitry behind it has not. Unfortunately, most of what is known about insects' brain activity comes from studies in species such as locusts or fruit flies. In these species, a region of the brain known as the central complex has been shown to have an essential role in homing behaviors. However, it is unknown how similar the central complex of bumblebees might be to fruit flies' or locusts', or how these differences may affect navigational abilities. Sayre et al. obtained images of thin slices of the bumblebee central complex using a technique called block-face electron microscopy, which produces high-resolution image volumes. These images were used to obtain a three-dimensional map of over 1300 neurons. This cellular atlas showed that key aspects of the central complex are nearly identical between flies and bumblebees, including the internal compass that monitors what direction the insect is travelling in. However, hundreds of millions of years of independent evolution have resulted in some differences. These were found in neurons possibly involved in forming memories of the directions and lengths of travelled paths, and in the circuits that use such vector memories to steer the insects towards their targets. Sayre et al. propose that these changes underlie bees' impressive ability to navigate. These results help explain how the structure of insects' brains can determine homing abilities. The insights gained could be used to develop efficient autonomous navigation systems, which are challenging to build and require a lot more processing power than offered by a small part of an insect brain.

A unified platform to manage, share, and archive morphological and functional data in insect neuroscience.

Insect neuroscience generates vast amounts of highly diverse data, of which only a small fraction are findable, accessible and reusable. To promote an open data culture, we have therefore developed the InsectBrainDatabase (IBdb), a free online platform for insect neuroanatomical and functional data. The IBdb facilitates biological insight by enabling effective cross-species comparisons, by linking neural structure with function, and by serving as general information hub for insect neuroscience. The IBdb allows users to not only effectively locate and visualize data, but to make them widely available for easy, automated reuse via an application programming interface. A unique private mode of the database expands the IBdb functionality beyond public data deposition, additionally providing the means for managing, visualizing, and sharing of unpublished data. This dual function creates an incentive for data contribution early in data management workflows and eliminates the additional effort normally associated with publicly depositing research data.

Insect neuroscience, like any field in the natural sciences, generates vast amounts of data. Currently, only a fraction are publicly available, and even less are reusable. This is because insect neuroscience data come in many formats and from many species. Some experiments focus on what insect brains look like (morphology), while others focus on how insect brains work (function). Some data come in the form of high-speed video, while other data contain voltage traces from individual neurons. Sharing is not as simple as uploading the raw files to the internet. To get a clear picture of how insect brains work, researchers need a way to cross-reference and connect different experiments. But, as it stands, there is no dedicated place for insect neuroscientists to share and explore such a diverse body of work. The community needs an open data repository that can link different types of data across many species, and can evolve as more data become available. Above all, this repository needs to be easy for researchers to use. To meet these specifications, Heinze et al. developed the Insect Brain Database. The database organizes data into three categories: species, brain structures, and neuron types. Within these categories, each entry has its own profile page. These pages bring different experiments together under one heading, allowing researchers to combine and compare data of different types. As researchers add more experiments, the profile pages will grow and evolve. To make the data easy to navigate, Heinze et al. developed a visual search tool. A combination of 2D and 3D images allow users to explore the data by anatomical location, without the need for expert knowledge. Researchers also have the option to upload their work in private mode, allowing them to securely share unpublished data. The Insect Brain Database brings data together in a way that is accessible not only to researchers, but also to students, and non-scientists. It will help researchers to find related work, to reuse existing data, and to build an open data culture. This has the potential to drive new discoveries combining research across the whole of the insect neuroscience field.

Why flies look to the skies.

Fruit flies rely on an intricate neural pathway to process polarized light signals in order to inform their internal compass about the position of the Sun.

Implementing an Insect Brain Computational Circuit Using III-V Nanowire Components in a Single Shared Waveguide Optical Network.

Recent developments in photonics include efficient nanoscale optoelectronic components and novel methods for subwavelength light manipulation. Here, we explore the potential offered by such devices as a substrate for neuromorphic computing. We propose an artificial neural network in which the weighted connectivity between nodes is achieved by emitting and receiving overlapping light signals inside a shared quasi 2D waveguide. This decreases the circuit footprint by at least an order of magnitude compared to existing optical solutions. The reception, evaluation, and emission of the optical signals are performed by neuron-like nodes constructed from known, highly efficient III-V nanowire optoelectronics. This minimizes power consumption of the network. To demonstrate the concept, we build a computational model based on an anatomically correct, functioning model of the central-complex navigation circuit of the insect brain. We simulate in detail the optical and electronic parts required to reproduce the connectivity of the central part of this network using previously experimentally derived parameters. The results are used as input in the full model, and we demonstrate that the functionality is preserved. Our approach points to a general method for drastically reducing the footprint and improving power efficiency of optoelectronic neural networks, leveraging the superior speed and energy efficiency of light as a carrier of information.

Visual Navigation: Ants Lose Track without Mushroom Bodies.

Ants use memorized visual scenes to navigate towards food sources and to return to their nest. Two new studies show that both of these behaviors fail when structures of the ant brain known as mushroom bodies are chemically disrupted, confirming long-held assumptions about the location of ants' visual navigation memories.

The head direction circuit of two insect species.

Recent studies of the Central Complex in the brain of the fruit fly have identified neurons with activity that tracks the animal's heading direction. These neurons are part of a neuronal circuit with dynamics resembling those of a ring attractor. The homologous circuit in other insects has similar topographic structure but with significant structural and connectivity differences. We model the connectivity patterns of two insect species to investigate the effect of these differences on the dynamics of the circuit. We illustrate that the circuit found in locusts can also operate as a ring attractor but differences in the inhibition pattern enable the fruit fly circuit to respond faster to heading changes while additional recurrent connections render the locust circuit more tolerant to noise. Our findings demonstrate that subtle differences in neuronal projection patterns can have a significant effect on circuit performance and illustrate the need for a comparative approach in neuroscience.

A Novel Major Output Target for Pheromone-Sensitive Projection Neurons in Male Moths.

Even though insects have comparably small brains, they achieve astoundingly complex behaviors. One example is flying moths tracking minute amounts of pheromones using olfactory circuits. The tracking distance can be up to 1 km, which makes it essential that male moths respond efficiently and reliably to very few pheromone molecules. The male-specific macroglomerular complex (MGC) in the moth antennal lobe contains circuitry dedicated to pheromone processing. Output neurons from this region project along three parallel pathways, the medial, mediolateral, and lateral tracts. The MGC-neurons of the lateral tract are least described and their functional significance is mainly unknown. We used mass staining, calcium imaging, and intracellular recording/staining to characterize the morphological and physiological properties of these neurons in the noctuid moth, Helicoverpa armigera. All lateral-tract MGC neurons targeted the column, a small region within the superior intermediate neuropil. We identified this region as a unique converging site for MGC lateral-tract neurons responsive to pheromones, as well as a dense congregating site for plant odor information since a substantial number of lateral-tract neurons from ordinary glomeruli (OG) also terminates in this region. The lateral-tract MGC-neurons responded with a shorter peak latency than the well-described neurons in the medial tract. Different from the medial-tract MGC neurons encoding odor quality important for species-specific signal identification, those in the lateral tract convey a more robust and rapid signal-potentially important for fast control of hard-wired behavior.

The brain of a nocturnal migratory insect, the Australian Bogong moth.

Every year, millions of Australian Bogong moths (Agrotis infusa) complete an astonishing journey: In Spring, they migrate over 1,000 km from their breeding grounds to the alpine regions of the Snowy Mountains, where they endure the hot summer in the cool climate of alpine caves. In autumn, the moths return to their breeding grounds, where they mate, lay eggs and die. These moths can use visual cues in combination with the geomagnetic field to guide their flight, but how these cues are processed and integrated into the brain to drive migratory behavior is unknown. To generate an access point for functional studies, we provide a detailed description of the Bogong moth's brain. Based on immunohistochemical stainings against synapsin and serotonin (5HT), we describe the overall layout as well as the fine structure of all major neuropils, including the regions that have previously been implicated in compass-based navigation. The resulting average brain atlas consists of 3D reconstructions of 25 separate neuropils, comprising the most detailed account of a moth brain to date. Our results show that the Bogong moth brain follows the typical lepidopteran ground pattern, with no major specializations that can be attributed to their spectacular migratory lifestyle. These findings suggest that migratory behavior does not require widespread modifications of brain structure, but might be achievable via small adjustments of neural circuitry in key brain areas. Locating these subtle changes will be a challenging task for the future, for which our study provides an essential anatomical framework.

The insect central complex and the neural basis of navigational strategies.

Oriented behaviour is present in almost all animals, indicating that it is an ancient feature that has emerged from animal brains hundreds of millions of years ago. Although many complex navigation strategies have been described, each strategy can be broken down into a series of elementary navigational decisions. In each moment in time, an animal has to compare its current heading with its desired direction and compensate for any mismatch by producing a steering response either to the right or to the left. Different from reflex-driven movements, target-directed navigation is not only initiated in response to sensory input, but also takes into account previous experience and motivational state. Once a series of elementary decisions are chained together to form one of many coherent navigation strategies, the animal can pursue a navigational target, e.g. a food source, a nest entrance or a constant flight direction during migrations. Insects show a great variety of complex navigation behaviours and, owing to their small brains, the pursuit of the neural circuits controlling navigation has made substantial progress over the last years. A brain region as ancient as insects themselves, called the central complex, has emerged as the likely navigation centre of the brain. Research across many species has shown that the central complex contains the circuitry that might comprise the neural substrate of elementary navigational decisions. Although this region is also involved in a wide range of other functions, we hypothesize in this Review that its role in mediating the animal's next move during target-directed behaviour is its ancestral function, around which other functions have been layered over the course of evolution.

Principles of Insect Path Integration.

Continuously monitoring its position in space relative to a goal is one of the most essential tasks for an animal that moves through its environment. Species as diverse as rats, bees, and crabs achieve this by integrating all changes of direction with the distance covered during their foraging trips, a process called path integration. They generate an estimate of their current position relative to a starting point, enabling a straight-line return, following what is known as a home vector. While in theory path integration always leads the animal precisely back home, in the real world noise limits the usefulness of this strategy when operating in isolation. Noise results from stochastic processes in the nervous system and from unreliable sensory information, particularly when obtaining heading estimates. Path integration, during which angular self-motion provides the sole input for encoding heading (idiothetic path integration), results in accumulating errors that render this strategy useless over long distances. In contrast, when using an external compass this limitation is avoided (allothetic path integration). Many navigating insects indeed rely on external compass cues for estimating body orientation, whereas they obtain distance information by integration of steps or optic-flow-based speed signals. In the insect brain, a region called the central complex plays a key role for path integration. Not only does the central complex house a ring-attractor network that encodes head directions, neurons responding to optic flow also converge with this circuit. A neural substrate for integrating direction and distance into a memorized home vector has therefore been proposed in the central complex. We discuss how behavioral data and the theoretical framework of path integration can be aligned with these neural data.

The Earth's Magnetic Field and Visual Landmarks Steer Migratory Flight Behavior in the Nocturnal Australian Bogong Moth.

Like many birds [1], numerous species of nocturnal moths undertake spectacular long-distance migrations at night [2]. Each spring, billions of Bogong moths (Agrotis infusa) escape hot conditions in different regions of southeast Australia by making a highly directed migration of over 1,000 km to a limited number of cool caves in the Australian Alps, historically used for aestivating over the summer [3, 4]. How moths determine the direction of inherited migratory trajectories at night and locate their destination (i.e., navigate) is currently unknown [5-7]. Here we show that Bogong moths can sense the Earth's magnetic field and use it in conjunction with visual landmarks to steer migratory flight behavior. By tethering migrating moths in an outdoor flight simulator [8], we found that their flight direction turned predictably when dominant visual landmarks and a natural Earth-strength magnetic field were turned together, but that the moths became disoriented within a few minutes when these cues were set in conflict. We thus conclude that Bogong moths, like nocturnally migrating birds [9], can use a magnetic sense. Our results represent the first reliable demonstration of the use of the Earth's magnetic field to steer flight behavior in a nocturnal migratory insect.