Insect Brain Research Articles

Correction to: 'A model of cue integration as vector summation in the insect brain' (2023) Mitchell et al.

Correction to: 'A model of cue integration as vector summation in the insect brain' (2023) Mitchell et al.

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.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing.

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Neuromorphic sequence learning with an event camera on routes through vegetation.

For many robotics applications, it is desirable to have relatively low-power and efficient onboard solutions. We took inspiration from insects, such as ants, that are capable of learning and following routes in complex natural environments using relatively constrained sensory and neural systems. Such capabilities are particularly relevant to applications such as agricultural robotics, where visual navigation through dense vegetation remains a challenging task. In this scenario, a route is likely to have high self-similarity and be subject to changing lighting conditions and motion over uneven terrain, and the effects of wind on leaves increase the variability of the input. We used a bioinspired event camera on a terrestrial robot to collect visual sequences along routes in natural outdoor environments and applied a neural algorithm for spatiotemporal memory that is closely based on a known neural circuit in the insect brain. We show that this method is plausible to support route recognition for visual navigation and more robust than SeqSLAM when evaluated on repeated runs on the same route or routes with small lateral offsets. By encoding memory in a spiking neural network running on a neuromorphic computer, our model can evaluate visual familiarity in real time from event camera footage.

Artificial nanophotonic neuron with internal memory for biologically inspired and reservoir network computing

Neurons with internal memory have been proposed for biological and bio-inspired neural networks, adding important functionality. We introduce an internal time-limited charge-based memory into a III–V nanowire (NW) based optoelectronic neural node circuit designed for handling optical signals in a neural network. The new circuit can receive inhibiting and exciting light signals, store them, perform a non-linear evaluation, and emit a light signal. Using experimental values from the performance of individual III–V NWs we create a realistic computational model of the complete artificial neural node circuit. We then create a flexible neural network simulation that uses these circuits as neuronal nodes and light for communication between the nodes. This model can simulate combinations of nodes with different hardware derived memory properties and variable interconnects. Using the full model, we simulate the hardware implementation for two types of neural networks. First, we show that intentional variations in the memory decay time of the nodes can significantly improve the performance of a reservoir network. Second, we simulate the implementation in an anatomically constrained functioning model of the central complex network of the insect brain and find that it resolves an important functionality of the network even with significant variations in the node performance. Our work demonstrates the advantages of an internal memory in a concrete, nanophotonic neural node. The use of variable memory time constants in neural nodes is a general hardware derived feature and could be used in a broad range of implementations.

Neuroarchitecture of the central complex in the Madeira cockroach Rhyparobia maderae: Pontine and columnar neuronal cell types.

Insects have evolved remarkable abilities to navigate over short distances and during long-range seasonal migrations. The central complex (CX) is a navigation center in the insect brain that controls spatial orientation and directed locomotion. It is composed of the protocerebral bridge (PB), the upper (CBU) and lower (CBL) division of the central body, and a pair of noduli. While most of its functional organization and involvement in head-direction coding has been obtained from work on flies, bees, and locusts that largely rely on vision for navigation, little contribution has been provided by work on nocturnal species. To close this gap, we have investigated the columnar organization of the CX in the cockroach Rhyparobia maderae. Rhyparobia maderae is a highly agile nocturnal insect that relies largely but not exclusively on antennal information for navigation. A particular feature of the cockroach CX is an organization of the CBU and CBL into interleaved series of eight and nine columns. Single-cell tracer injections combined with imaging and 3D analysis revealed five systems of pontine neurons connecting columns along the vertical and horizontal axis and 18 systems of columnar neurons with topographically organized projection patterns. Among these are six types of neurons with no correspondence in other species. Many neurons send processes into the anterior lip, a brain area highly reduced in bees and unknown in flies. While sharing many features with the CX in other species, the cockroach CX shows some unique attributes that may be related to the ecological niche of this insect.

Altered synaptic organization in the mushroom bodies of honey bees exposed as foragers to the pesticide fipronil

The pesticide fipronil is a GABA receptor antagonist that induces hyperexcitability in the insect nervous system. Its use is controversial because unintentional fipronil exposure may contribute to the ongoing global decline of pollinator populations. Sublethal doses of fipronil have been tentatively linked to reduced colony fitness and impaired learning in the western honey bee, Apis mellifera. The mushroom bodies, insect brain centers important for association learning and memory, contain fipronil-sensitive receptors and may therefore be directly affected by this pesticide. We investigated the synaptic organization of the mushroom bodies in worker honey bees exposed to fipronil using immunolabeling for a pre-synaptic marker and laser scanning confocal microscopy. Exposure of honey bee foragers to fipronil at a feasible field-realistic (1 ppb) concentration decreased the estimated density of immunolabeled microglomerular synaptic complexes in the lip and collar neuropil regions of the mushroom bodies. Effects were also evident after lower (0.1 ppb) and higher (4 ppb) exposures. Other indicators of synaptic organization (bouton number, surface area) were altered by exposure to fipronil in a dose-dependent fashion. These results indicate that sublethal doses of fipronil can result in atypical synaptic organization in the mushroom bodies of honey bees and suggest a mechanism by which fipronil, through perturbation of mushroom body-dependent functions, might diminish honey bee colony survival.

Comparative morphology of serotonin-immunoreactive neurons innervating the central complex in the brain of dicondylian insects.

Serotonin (5-hydroxytryptamine) acts as a widespread neuromodulator in the nervous system of vertebrates and invertebrates. In insects, it promotes feeding, enhances olfactory sensitivity, modulates aggressive behavior, and, in the central complex of Drosophila, serves a role in sleep homeostasis. In addition to a role in sleep-wake regulation, the central complex has a prominent role in spatial orientation, goal-directed locomotion, and navigation vector memory. To further understand the role of serotonergic signaling in this brain area, we analyzed the distribution and identity of serotonin-immunoreactive neurons across a wide range of insect species. While one bilateral pair of tangential neurons innervating the central body was present in all species studied, a second type was labeled in all neopterans but not in dragonflies and firebrats. Both cell types show conserved major fiber trajectories but taxon-specific differences in dendritic targets outside the central body and axonal terminals in the central body, noduli, and lateral accessory lobes. In addition, numerous tangential neurons of the protocerebral bridge were labeled in all studied polyneopteran species except for Phasmatodea, but not in Holometabola. Lepidoptera and Diptera showed additional labeling of two bilateral pairs of neurons of a third type. The presence of serotonin in systems of columnar neurons apparently evolved independently in dragonflies and desert locusts. The data suggest distinct evolutionary changes in the composition of serotonin-immunolabeled neurons of the central complex and provides a promising basis for a phylogenetic study in a wider range of arthropod species.

Expansion microscopy in honeybee brains for high-resolution neuroanatomical analyses in social insects

The diffraction limit of light microscopy poses a problem that is frequently faced in structural analyses of social insect brains. With the introduction of expansion microscopy (ExM), a tool became available to overcome this limitation by isotropic physical expansion of preserved specimens. Our analyses focus on synaptic microcircuits (microglomeruli, MG) in the mushroom body (MB) of social insects, high-order brain centers for sensory integration, learning, and memory. MG undergo significant structural reorganizations with age, sensory experience, and during long-term memory formation. However, the changes in subcellular architecture involved in this plasticity have only partially been accessed yet. Using the western honeybee Apis mellifera as an experimental model, we established ExM for the first time in a social insect species and applied it to investigate plasticity in synaptic microcircuits within MG of the MB calyces. Using combinations of antibody staining and neuronal tracing, we demonstrate that this technique enables quantitative and qualitative analyses of structural neuronal plasticity at high resolution in a social insect brain.

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.

How honey bees make fast and accurate decisions.

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

Transcriptional changes in specific subsets of Drosophila neurons following inhibition of the serotonin transporter

The transcriptional effects of SSRIs and other serotonergic drugs remain unclear, in part due to the heterogeneity of postsynaptic cells, which may respond differently to changes in serotonergic signaling. Relatively simple model systems such as Drosophila afford more tractable microcircuits in which to investigate these changes in specific cell types. Here, we focus on the mushroom body, an insect brain structure heavily innervated by serotonin and comprised of multiple different but related subtypes of Kenyon cells. We use fluorescence-activated cell sorting of Kenyon cells, followed by either bulk or single-cell RNA sequencing to explore the transcriptomic response of these cells to SERT inhibition. We compared the effects of two different Drosophila Serotonin Transporter (dSERT) mutant alleles as well as feeding the SSRI citalopram to adult flies. We find that the genetic architecture associated with one of the mutants contributed to significant artefactual changes in expression. Comparison of differential expression caused by loss of SERT during development versus aged, adult flies, suggests that changes in serotonergic signaling may have relatively stronger effects during development, consistent with behavioral studies in mice. Overall, our experiments revealed limited transcriptomic changes in Kenyon cells, but suggest that different subtypes may respond differently to SERT loss-of-function. Further work exploring the effects of SERT loss-of-function in other circuits may be used help to elucidate how SSRIs differentially affect a variety of different neuronal subtypes both during development and in adults.

Granger Causality Analysis of Transient Calcium Dynamics in the Honey Bee Antennal Lobe Network.

Odorant processing presents multiple parallels across animal species, and insects became relevant models for the study of olfactory coding because of the tractability of the underlying neural circuits. Within the insect brain, odorants are received by olfactory sensory neurons and processed by the antennal lobe network. Such a network comprises multiple nodes, named glomeruli, that receive sensory information and are interconnected by local interneurons participating in shaping the neural representation of an odorant. The study of functional connectivity between the nodes of a sensory network in vivo is a challenging task that requires simultaneous recording from multiple nodes at high temporal resolutions. Here, we followed the calcium dynamics of antennal lobe glomeruli and applied Granger causality analysis to assess the functional connectivity among network nodes in the presence and absence of an odorous stimulus. This approach revealed the existence of causal connectivity links between antennal lobe glomeruli in the absence of olfactory stimulation, while at odor arrival, the connectivity network's density increased and became stimulus-specific. Thus, such an analytical approach may provide a new tool for the investigation of neural network plasticity in vivo.

Walking bumblebees see faster.

The behavioural state of animals has profound effects on neuronal information processing. Locomotion changes the response properties of visual interneurons in the insect brain, but it is still unknown if it also alters the response properties of photoreceptors. Photoreceptor responses become faster at higher temperatures. It has therefore been suggested that thermoregulation in insects could improve temporal resolution in vision, but direct evidence for this idea has so far been missing. Here, we compared electroretinograms from the compound eyes of tethered bumblebees that were either sitting or walking on an air-supported ball. We found that the visual processing speed strongly increased when the bumblebees were walking. By monitoring the eye temperature during recording, we saw that the increase in response speed was in synchrony with a rise in eye temperature. By artificially heating the head, we show that the walking-induced temperature increase of the visual system is sufficient to explain the rise in processing speed. We also show that walking accelerates the visual system to the equivalent of a 14-fold increase in light intensity. We conclude that the walking-induced rise in temperature accelerates the processing of visual information-an ideal strategy to process the increased information flow during locomotion.

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.

Multiplexed neuropeptide mapping in ant brains integrating microtomography and three-dimensional mass spectrometry imaging.

Neuropeptides are important regulators of animal physiology and behavior. Hitherto the gold standard for the localization of neuropeptides have been immunohistochemical methods that require the synthesis of antibody panels, while another limiting factor has been the brain's opacity for subsequent in situ light or fluorescence microscopy. To address these limitations, we explored the integration of high-resolution mass spectrometry imaging (MSI) with microtomography for a multiplexed mapping of neuropeptides in two evolutionary distant ant species, Atta sexdens and Lasius niger. For analyzing the spatial distribution of chemically diverse peptide molecules across the brain in each species, the acquisition of serial mass spectrometry images was essential. As a result, we have comparatively mapped the three-dimensional (3D) distributions of eight conserved neuropeptides throughout the brain microanatomy. We demonstrate that integrating the 3D MSI data into high-resolution anatomy models can be critical for studying organs with high plasticity such as brains of social insects. Several peptides, like the tachykinin-related peptides (TK) 1 and 4, were widely distributed in many brain areas of both ant species, whereas others, for instance myosuppressin, were restricted to specific regions only. Also, we detected differences at the species level; many peptides were identified in the optic lobe of L. niger, but only one peptide (ITG-like) was found in this region in A. sexdens. Building upon MS imaging studies on neuropeptides in invertebrate model systems, our approach leverages correlative MSI and computed microtomography for investigating fundamental neurobiological processes by visualizing the unbiased 3D neurochemistry in its complex anatomic environment.

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.

3D atlas of cerebral neuropils with previously unknown demarcations in the honey bee brain.

Honey bees (Apis mellifera) express remarkable social interactions and cognitive capabilities that have been studied extensively. In many cases, behavioral studies were accompanied by neurophysiological and neuroanatomical investigations. While most studies have focused on primary sensory neuropils, such as the optic lobes or antennal lobes, and major integration centers, such as the mushroom bodies or the central complex, many regions of the cerebrum (the central brain without the optic lobes) of the honey bee are only poorly explored so far, both anatomically and physiologically. To promote studies of these brain regions, we used anti-synapsin immunolabeling and neuronal tract tracings followed by confocal imaging and 3D reconstructions to demarcate all neuropils in the honey bee cerebrum and close this gap at the anatomical level. We demarcated 35 neuropils and 25 fiber tracts in the honey bee cerebrum, most of which have counterparts in the fly (Drosophila melanogaster) and other insect species that have been investigated so far at this level of detail. We discuss the role of cerebral neuropils in multisensory integration in the insect brain, emphasize the importance of this brain atlas for comparative studies, and highlight specific architectural features of the honey bee cerebrum.

Pesticide makes cockroaches slow down and forget

Farmers have been waging war against pests since humans first started planting crops. More recently, advances in pesticides have curbed many of the crop losses that farmers have been experiencing, which has helped the planet's population to grow to 8 billion people. However, some of the pesticides come with a cost; they inadvertently kill pollinator species which the agriculture industry relies upon to fertilize their crops. Not only do many pesticides have unintentional victims but they also can remain in the groundwater for some time, thereby affecting insects that don't come into direct contact with the treated plants. Though the amount of pesticide that makes its way into the water supply is much less than the amount that is sprayed onto a plant, these smaller doses could still have dire consequences for other insects. With this in mind, Maria Rosa of the Universidade Federal do Pampa (UNIPAMPA), Brazil, and Cháriston Dal Belo of the Universidade Federal de São Paulo, Brazil, turned to the speckled cockroach (Nauphoeta cinerea) to help them answer whether smaller doses of the pesticide fipronil affected these non-target insects.Working with other scientists from UNIPAMPA, the Universidade Estadual de Campinas, Brazil, and the University of Oslo, Norway, Rosa and Dal Belo first gave the cockroaches different amounts of fipronil before measuring how many times they cleaned their legs and antennae in 30 minutes. The cockroaches didn't groom their legs as much when they were given fipronil. According to Rosa, ‘grooming in insects is associated with body cleanliness and courtship’, among other behaviours, and not spending time grooming could lead to a shorter lifespan and fewer offspring. In addition, the researchers measured how far the insects walked versus how much time they spent stationary in a 10 minute video. When given the pesticide, the cockroaches didn't explore as much and spent more time stationary, even at the lowest doses of fipronil. Not spending time moving or exploring could cause these insects to be unable to find food or escape from predators. As the cockroaches weren't moving as much, Rosa and Dal Belo wondered what was causing this lack of locomotion.To get to the root of this, the duo measured how hard the muscles of the cockroach's legs contracted. With the highest dose of fipronil, the legs had trouble contracting, therefore reducing the animal's mobility and potentially hampering their ability to find a meal. But it isn't just movement that fipronil affects. Because of the way that fipronil interacts with the insect's brain, the duo were also interested in how the pesticide might affect how well the cockroaches remembered certain smells. Normally, cockroaches are repulsed by the smell of citronella, but they can learn to associate this odour with the reward of a sugar solution, causing them to move towards the smell. However, if the insects were given fipronil beforehand, they couldn't learn to associate citronella with the sugary reward. Being unable to learn to associate smells with a reward could have devastating effects on an animal's ability to find food or mates.While Rosa and colleagues utilized the nearly indestructible cockroach to study the effects of this particular pesticide, they are quick to point out that their findings are likely true for other insect species as well. While using pesticides definitely helps our crop yields, it could also have the unintended yet devastating side-effect of decimating the number of pollinator species such as bees and butterflies, which could be even more disastrous for humans than allowing a few crops to be eaten by pests.