Insect Brain Research Articles

Olfactory coding in the mosquito antennal lobe: labeled lines or combinatorial code?

Odors serve as important cues for many behaviors in mosquitoes, including host-seeking, foraging, and oviposition. They are detected by olfactory receptor neurons present on the sensory organs, whose axons take this signal to the antennal lobe, the first olfactory processing center in the insect brain. We review the organization and the functioning of the antennal lobe in mosquitoes, focusing on two populations of interneurons present there: the local neurons (LNs) and the projection neurons (PNs). LNs enable information processing in the antennal lobe by providing lateral inhibition and excitation. PNs carry the processed output to downstream neurons in the lateral horn and the mushroom body. We compare the ideas of labeled lines and combinatorial codes, and argue that the PN population encodes odors combinatorially. Throughout this review, we discuss the observations from Aedes, Anopheles, and Culex mosquitoes in the context of previous findings from Drosophila and other insects.

The brain atlas of a subsocial bee reflects that of eusocial Hymenoptera.

The evolutionary transition from solitary life to group-living in a society with cooperative brood care, reproductive division of labor and morphological castes is associated with increased cognitive demands for task-specialization. Associated with these demands, the brains of eusocial Hymenoptera divide transcriptomic signatures associated with foraging and reproduction to different populations of cells and also show diverse astrocyte and Kenyon cell types compared with solitary non-hymenopteran insects. The neural architecture of subsocial bees, which represent evolutionary antecedent states to eusocial Hymenoptera, could then show how widely this eusocial brain is conserved across aculeate Hymenoptera. Using single-nucleus transcriptomics, we have created an atlas of neuron and glial cell types from the brain of a subsocial insect, the small carpenter bee (Ceratina calcarata). The proportion of C. calcarata neurons related to the metabolism of classes of neurotransmitters is similar to that of other insects, whereas astrocyte and Kenyon cell types show highly similar gene expression patterns to those of eusocial Hymenoptera. In the winter, the transcriptomic signature across the brain reflected diapause. When the bee was active in the summer, however, genes upregulated in neurons reflected foraging, while the gene expression signature of glia associated with reproductive functions. Like eusocial Hymenoptera, we conclude that neural components for foraging and reproduction in C. calcarata are compartmentalized to different parts of its brain. Cellular examination of the brains of other solitary and subsocial insects can show the extent of neurobiological conservation across levels of social complexity.

A historical perspective on the insect central complex: Anatomy, development, and function

The central complex (CX), a remarkable brain region at the core of insect behaviors, has been the subject of extensive research for decades. In this review, we offer a comprehensive historical perspective on the anatomy, development, and function of the CX. The CX consists of discrete and highly structured neuropils found at the center of the brain, which are conserved across insects and arthropods. The developmental processes that shape the CX are themselves conserved across insects. In early research, the CX had been shown to receive visual information and control motor function. Using increasingly advanced methods throughout the years, it has become clear that the CX is involved in high-level behavioral control, such as in vector navigation and goal directed orientation. Its numerical simplicity presents a rare opportunity to study structure-function relationships in small brains, gain insights into evolutionary neurobiology, and develop novel neuromorphic technologies inspired by insect brains. Since the CX is a highly conserved brain region involved in the control of spatial tasks, it is uniquely suited to gain a detailed understanding of the computations required for these processes at the level of neural circuits.

Cell type-specific driver lines targeting the Drosophila central complex and their use to investigate neuropeptide expression and sleep regulation.

The central complex (CX) plays a key role in many higher-order functions of the insect brain including navigation and activity regulation. Genetic tools for manipulating individual cell types, and knowledge of what neurotransmitters and neuromodulators they express, will be required to gain mechanistic understanding of how these functions are implemented. We generated and characterized split-GAL4 driver lines that express in individual or small subsets of about half of CX cell types. We surveyed neuropeptide and neuropeptide receptor expression in the central brain using fluorescent in situ hybridization. About half of the neuropeptides we examined were expressed in only a few cells, while the rest were expressed in dozens to hundreds of cells. Neuropeptide receptors were expressed more broadly and at lower levels. Using our GAL4 drivers to mark individual cell types, we found that 51 of the 85 CX cell types we examined expressed at least one neuropeptide and 21 expressed multiple neuropeptides. Surprisingly, all co-expressed a small neurotransmitter. Finally, we used our driver lines to identify CX cell types whose activation affects sleep, and identified other central brain cell types that link the circadian clock to the CX. The well-characterized genetic tools and information on neuropeptide and neurotransmitter expression we provide should enhance studies of the CX.

Reinforcement learning as a robotics-inspired framework for insect navigation: from spatial representations to neural implementation.

Bees are among the master navigators of the insect world. Despite impressive advances in robot navigation research, the performance of these insects is still unrivaled by any artificial system in terms of training efficiency and generalization capabilities, particularly considering the limited computational capacity. On the other hand, computational principles underlying these extraordinary feats are still only partially understood. The theoretical framework of reinforcement learning (RL) provides an ideal focal point to bring the two fields together for mutual benefit. In particular, we analyze and compare representations of space in robot and insect navigation models through the lens of RL, as the efficiency of insect navigation is likely rooted in an efficient and robust internal representation, linking retinotopic (egocentric) visual input with the geometry of the environment. While RL has long been at the core of robot navigation research, current computational theories of insect navigation are not commonly formulated within this framework, but largely as an associative learning process implemented in the insect brain, especially in the mushroom body (MB). Here we propose specific hypothetical components of the MB circuit that would enable the implementation of a certain class of relatively simple RL algorithms, capable of integrating distinct components of a navigation task, reminiscent of hierarchical RL models used in robot navigation. We discuss how current models of insect and robot navigation are exploring representations beyond classical, complete map-like representations, with spatial information being embedded in the respective latent representations to varying degrees.

Lipases are differentially regulated by hormones to maintain free fatty acid homeostasis for insect brain development

BackgroundFree fatty acids (FFAs) play vital roles as energy sources and substrates in organisms; however, the molecular mechanism regulating the homeostasis of FFA levels in various circumstances, such as feeding and nonfeeding stages, is not fully clarified. Holometabolous insects digest dietary triglycerides (TAGs) during larval feeding stages and degrade stored TAGs in the fat body during metamorphosis after feeding cessation, which presents a suitable model for this study.ResultsThis study reported that two lipases are differentially regulated by hormones to maintain the homeostasis of FFA levels during the feeding and nonfeeding stages using the lepidopteran insect cotton bollworm Helicoverpa armigera as a model. Lipase member H-A-like (Lha-like), related to human pancreatic lipase (PTL), was abundantly expressed in the midgut during the feeding stage, while the monoacylglycerol lipase ABHD12-like (Abhd12-like), related to human monoacylglycerol lipase (MGL), was abundantly expressed in the fat body during the nonfeeding stage. Lha-like was upregulated by juvenile hormone (JH) via the JH intracellular receptor methoprene-tolerant 1 (MET1), and Abhd12-like was upregulated by 20-hydroxyecdysone (20E) via forkhead box O (FOXO) transcription factor. Knockdown of Lha-like decreased FFA levels in the hemolymph and reduced TAG levels in the fat body. Moreover, lipid droplets (LDs) were small, the brain morphology was abnormal, the size of the brain was small, and the larvae showed the phenotype of delayed pupation, small pupae, and delayed tissue remodeling. Knockdown of Abhd12-like decreased FFA levels in the hemolymph; however, TAG levels increased in the fat body, and LDs remained large. The development of the brain was arrested at the larval stage, and the larvae showed a delayed pupation phenotype and delayed tissue remodeling.ConclusionsThe differential regulation of lipases expression by different hormones determines FFAs homeostasis and different TAG levels in the fat body during the feeding larval growth and nonfeeding stages of metamorphosis in the insect. The homeostasis of FFAs supports insect growth, brain development, and metamorphosis.

Structural changes shaping the Drosophila ellipsoid body ER-neurons during development and aging

The ellipsoid body (EB) of the insect brain performs pivotal functions in controlling navigation. Input and output of the EB is provided by multiple classes of R-neurons (now referred to as ER-neurons) and columnar neurons which interact with each other in a stereotypical and spatially highly ordered manner. The developmental mechanisms that control the connectivity and topography of EB neurons are largely unknown. One indispensable prerequisite to unravel these mechanisms is to document in detail the sequence of events that shape EB neurons during their development. In this study, we analyzed the development of the Drosophila EB. In addition to globally following the ER-neuron and columnar neuron (sub)classes in the spatial context of their changing environment we performed a single cell analysis using the multi-color flip out (MCFO) system to analyze the developmental trajectory of ER-neurons at different pupal stages, young adults (4d) and aged adults (∼60d). We show that the EB develops as a merger of two distinct elements, a posterior and anterior EB primordium (prEBp and prEBa, respectively. ER-neurons belonging to different subclasses form growth cones and filopodia that associate with the prEBp and prEBa in a pattern that, from early pupal stages onward, foreshadows their mature structure. Filopodia of all ER-subclasses are initially much longer than the dendritic and terminal axonal branches they give rise to, and are pruned back during late pupal stages. Interestingly, extraneous branches, particularly significant in the dendritic domain, are a hallmark of ER-neuron structure in aged brains. Aging is also associated with a decline in synaptic connectivity from columnar neurons, as well as upregulation of presynaptic protein (Brp) in ER-neurons. Our findings advance the EB (and ER-neurons) as a favorable system to visualize and quantify the development and age-related decline of a complex neuronal circuitry.

NERVOUS SYSTEM OF A PIGEON SLENDER LOUSE COLUMBICOLA COLUMBAE (PHTHIRAPTERA: ISCHNOCERA)

The nervous system of a pigeon slender louse, Columbicola columbae, has been studied in greater detail. C. columbae is a permanent, obligatory, and wingless insect. The central nervous system consists of a series of ganglia that supply nerves to successive body segments. The three main ganglia in the head, protocerebrum, deutocerebrum, and tritocerebrum, are fused to form the brain or supraesophageal ganglion. The nervous system of the pigeon slender louse, C. columbae (Phthiraptera: Ischnocera), consists of a U-shaped compact cerebral ganglion, subesophageal ganglion, and three thoracic ganglia. The ventral nerve cord and subesophageal ganglion are also located in the head. The three thoracic ganglions are placed in pro-, meso-, and meta-thorax. The frontal ganglion is situated anterior to the brain at a considerable distance.. KEYWORDS :Brain, Columbicola columbae, Nervous system, Pigeon slender louse

Investigating visual navigation using spiking neural network models of the insect mushroom bodies.

Ants are capable of learning long visually guided foraging routes with limited neural resources. The visual scene memory needed for this behaviour is mediated by the mushroom bodies; an insect brain region important for learning and memory. In a visual navigation context, the mushroom bodies are theorised to act as familiarity detectors, guiding ants to views that are similar to those previously learned when first travelling along a foraging route. Evidence from behavioural experiments, computational studies and brain lesions all support this idea. Here we further investigate the role of mushroom bodies in visual navigation with a spiking neural network model learning complex natural scenes. By implementing these networks in GeNN-a library for building GPU accelerated spiking neural networks-we were able to test these models offline on an image database representing navigation through a complex outdoor natural environment, and also online embodied on a robot. The mushroom body model successfully learnt a large series of visual scenes (400 scenes corresponding to a 27 m route) and used these memories to choose accurate heading directions during route recapitulation in both complex environments. Through analysing our model's Kenyon cell (KC) activity, we were able to demonstrate that KC activity is directly related to the respective novelty of input images. Through conducting a parameter search we found that there is a non-linear dependence between optimal KC to visual projection neuron (VPN) connection sparsity and the length of time the model is presented with an image stimulus. The parameter search also showed training the model on lower proportions of a route generally produced better accuracy when testing on the entire route. We embodied the mushroom body model and comparator visual navigation algorithms on a Quanser Q-car robot with all processing running on an Nvidia Jetson TX2. On a 6.5 m route, the mushroom body model had a mean distance to training route (error) of 0.144 ± 0.088 m over 5 trials, which was performance comparable to standard visual-only navigation algorithms. Thus, we have demonstrated that a biologically plausible model of the ant mushroom body can navigate complex environments both in simulation and the real world. Understanding the neural basis of this behaviour will provide insight into how neural circuits are tuned to rapidly learn behaviourally relevant information from complex environments and provide inspiration for creating bio-mimetic computer/robotic systems that can learn rapidly with low energy requirements.

Evolution of neural circuitry and cognition.

Neural circuits govern the interface between the external environment, internal cues and outwardly directed behaviours. To process multiple environmental stimuli and integrate these with internal state requires considerable neural computation. Expansion in neural network size, most readily represented by whole brain size, has historically been linked to behavioural complexity, or the predominance of cognitive behaviours. Yet, it is largely unclear which aspects of circuit variation impact variation in performance. A key question in the field of evolutionary neurobiology is therefore how neural circuits evolve to allow improved behavioural performance or innovation. We discuss this question by first exploring how volumetric changes in brain areas reflect actual neural circuit change. We explore three major axes of neural circuit evolution-replication, restructuring and reconditioning of cells and circuits-and discuss how these could relate to broader phenotypes and behavioural variation. This discussion touches on the relevant uses and limitations of volumetrics, while advocating a more circuit-based view of cognition. We then use this framework to showcase an example from the insect brain, the multi-sensory integration and internal processing that is shared between the mushroom bodies and central complex. We end by identifying future trends in this research area, which promise to advance the field of evolutionary neurobiology.

An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context.

The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.

Insights from the past: the work of Hans von Alten on the evolution of brain structure, ecological adaptation, and cognition in hymenopteran species.

In his treatise on arthropod brains, Hans von Alten (1910) focuses on a specific functional group of insects-the flying Hymenoptera-which exhibit a spectrum of lifestyles ranging from solitary to social. His work presents a distinctive comparative neuro-anatomical approach rooted in an eco-evolutionary and eco-behavioral background. We regard his publication as an exceptionally valuable source of information and seek to inspire the research community dedicated to the study of the insect brain to explore its insights further, even after more than 110 years. We have translated and annotated his work, expecting it to engage researchers not just with its remarkable drawings but also with its substantive content and exemplary research strategy. The present text is designed to complement von Alten's publication, situating it within the temporal context of nineteenth-century and early twentieth-century studies, and to draw connections to contemporary perspectives, especially concerning a central brain structure: the mushroom body.

Reinforcement expectation in the honeybee (Apis mellifera): Can downshifts in reinforcement show conditioned inhibition?

When animals learn the association of a conditioned stimulus (CS) with an unconditioned stimulus (US), later presentation of the CS invokes a representation of the US. When the expected US fails to occur, theoretical accounts predict that conditioned inhibition can accrue to any other stimuli that are associated with this change in the US. Empirical work with mammals has confirmed the existence of conditioned inhibition. But the way it is manifested, the conditions that produce it, and determining whether it is the opposite of excitatory conditioning are important considerations. Invertebrates can make valuable contributions to this literature because of the well-established conditioning protocols and access to the central nervous system (CNS) for studying neural underpinnings of behavior. Nevertheless, although conditioned inhibition has been reported, it has yet to be thoroughly investigated in invertebrates. Here, we evaluate the role of the US in producing conditioned inhibition by using proboscis extension response conditioning of the honeybee (Apis mellifera). Specifically, using variations of a "feature-negative" experimental design, we use downshifts in US intensity relative to US intensity used during initial excitatory conditioning to show that an odorant in an odor-odor mixture can become a conditioned inhibitor. We argue that some alternative interpretations to conditioned inhibition are unlikely. However, we show variation across individuals in how strongly they show conditioned inhibition, with some individuals possibly revealing a different means of learning about changes in reinforcement. We discuss how the resolution of these differences is needed to fully understand whether and how conditioned inhibition is manifested in the honeybee, and whether it can be extended to investigate how it is encoded in the CNS. It is also important for extension to other insect models. In particular, work like this will be important as more is revealed of the complexity of the insect brain from connectome projects.

What do the mushroom bodies do for the insect brain? Twenty-five years of progress.

In 1998, a special edition of Learning & Memory was published with a discrete focus of synthesizing the state of the field to provide an overview of the function of the insect mushroom body. While molecular neuroscience and optical imaging of larger brain areas were advancing, understanding the basic functioning of neuronal circuits, particularly in the context of the mushroom body, was rudimentary. In the past 25 years, technological innovations have allowed researchers to map and understand the in vivo function of the neuronal circuits of the mushroom body system, making it an ideal model for investigating the circuit basis of sensory encoding, memory formation, and behavioral decisions. Collaborative efforts within the community have played a crucial role, leading to an interactive connectome of the mushroom body and accessible genetic tools for studying mushroom body circuit function. Looking ahead, continued technological innovation and collaborative efforts are likely to further advance our understanding of the mushroom body and its role in behavior and cognition, providing insights that generalize to other brain structures and species.

Unique spatially and temporary-regulated/sex-specific expression of a long ncRNA, Nb-1, suggesting its pleiotropic functions associated with honey bee lifecycle

Honey bees are social insects, and each colony member has unique morphological and physiological traits associated with their social tasks. Previously, we identified a long non-coding RNA from honey bees, termed Nb-1, whose expression in the brain decreases associated with the age-polyethism of workers and is detected in some neurosecretory cells and octopaminergic neurons, suggesting its role in the regulation of worker labor transition. Herein, we investigated its spatially and temporary-regulated/sex-specific expression. Nb-1 was expressed as an abundant maternal RNA during oogenesis and embryogenesis in both sexes. In addition, Nb-1 was expressed preferentially in the proliferating neuroblasts of the mushroom bodies (a higher-order center of the insect brain) in the pupal brains, suggesting its role in embryogenesis and mushroom body development. On the contrary, Nb-1 was expressed in a drone-specific manner in the pupal and adult retina, suggesting its role in the drone visual development and/or sense. Subcellular localization of Nb-1 in the brain during development differed depending on the cell type. Considering that Nb-1 is conserved only in Apidae, our findings suggest that Nb-1 potentially has pleiotropic functions in the expression of multiple developmental, behavioral, and physiological traits, which are closely associated with the honey bee lifecycle.

Cover Caption

AbstractIn the fascinating realm of insect neuroscience, researchers are achieving remarkable breakthroughs by delving into the complexities of the insect brain, which, despite its minuscule size, showcases an astonishing level of complexity. Utilizing the advanced methodology of single‐cell RNA‐sequencing, scientists are now able to dissect the brain's intricate cellular architecture at an unprecedented resolution. This sophisticated technique reveals the distinct roles individual cells play in governing behaviors such as learning, memory, and social interactions. Through meticulous mapping of various cell types and their interconnections, these pioneering studies not only deepen our comprehension of insect behavior but also propel the field of neuroscience into new frontiers (see pages 314–327). Image provided by Hao Zheng.

Transgenic line for characterizing GABA-receptor expression to study the neural basis of olfaction in the yellow-fever mosquito.

The mosquito Aedes aegypti is an important vector of diseases including dengue, Zika, chikungunya, and yellow fever. Olfaction is a critical modality for mosquitoes enabling them to locate hosts, sources of nectar, and sites for oviposition. GABA is an essential neurotransmitter in olfactory processing in the insect brain, including the primary olfactory center, the antennal lobe. Previous work with Ae. aegypti has suggested that antennal lobe inhibition via GABA may be involved in the processing of odors. However, little is known about GABA receptor expression in the mosquito brain, or how they may be involved in odor attraction. In this context, generating mutants that target the mosquito's olfactory responses, and particularly the GABAergic system, is essential to achieve a better understanding of these diverse processes and olfactory coding in these disease vectors. Here we demonstrate the potential of a transgenic line using the QF2 transcription factor, GABA-B1QF2-ECFP, as a new neurogenetic tool to investigate the neural basis of olfaction in Ae. aegypti. Our results show that the gene insertion has a moderate impact on mosquito fitness. Moreover, the line presented here was crossed with a QUAS reporter line expressing the green fluorescent protein and used to determine the location of the metabotropic GABA-B1 receptor expression. We find high receptor expression in the antennal lobes, especially the cell bodies surrounding the antennal lobes. In the mushroom bodies, receptor expression was high in the Kenyon cells, but had low expression in the mushroom body lobes. Behavioral experiments testing the fruit odor attractants showed that the mutants lost their behavioral attraction. Together, these results show that the GABA-B1QF2-ECFP line provides a new tool to characterize GABAergic systems in the mosquito nervous system.

Neuroplasticity in honey bee brains: An enhanced micro-computed tomography protocol for precise mushroom body volume measurement

BackgroundIn insect brains, mushroom bodies are associated with memory and learning behavior. It has been demonstrated that the volume of the mushroom bodies in the brain of a worker honey bee changes during the adult stage. Changes in mushroom body volume imply high neuroplasticity in the brains and may be related to the age polyethism of honey bees. A suitable volume measurement method is needed to understand the correlation between behavioral changes and mushroom body volume changes in honey bees. New methodWe developed a new protocol for insect micro-computed tomography by modifying a previously reported method. Permount™ mounting medium was used as the embedding medium for micro-computed tomography scanning. ResultsThis protocol can generate images with high contrast inside the brain and reduce the marked shape changes during specimen processing. From the resulting high-contrast images, we used freeware to generate a three-dimensional model and calculate the volumes of the mushroom bodies in honey bees. The measured volumes of the mushroom bodies were larger than the values reported in most previous studies. There was no significant difference between the left and right mushroom body volumes, but the volumes of honey bee mushroom bodies significantly increased with age. Comparison with existing methodsPrevious protocols for micro-computed tomography using dried samples would cause brain shrinkage; protocols using ethanol-preserved or resin-embedded samples generated images with lower contrast. ConclusionsThe embedding protocol for micro-computed tomography is suitable for calculating volume of the mushroom bodies in honey bee brains.

Gene regulation supporting sociality shared across lineages and variation in complexity.

Across evolutionary lineages, insects vary in social complexity, from those that exhibit extended parental care to those with elaborate divisions of labor. Here, we synthesize the sociogenomic resources from hundreds of species to describe common gene regulatory mechanisms in insects that regulate social organization across phylogeny and levels of social complexity. Different social phenotypes expressed by insects can be linked to the organization of co-expressing gene networks and features of the epigenetic landscape. Insect sociality also stems from processes like the emergence of parental care and the decoupling of ancestral genetic programs. One underexplored avenue is how variation in a group's social environment affects the gene expression of individuals. Additionally, an experimental reduction of gene expression would demonstrate how the activity of specific genes contributes to insect social phenotypes. While tissue specificity provides greater localization of the gene expression underlying social complexity, emerging transcriptomic analysis of insect brains at the cellular level provides even greater resolution to understand the molecular basis of social insect evolution.

COMPARATIVE NEUROANATOMY OF DESCENDING NEURONS OF THE SUPRAESOPHAGEAL GANGLION OF COCKROACHES OF THE FAMILY BLABERIDAE (BLATTODEA)

A comparative study of the morphology of descending neurons connecting the supraesophageal ganglion and thoracic ganglia in cockroaches of the family Blaberidae, which differ in protective behavior and flight ability, was carried out. The neuronal structure of these families was compared with the descending neurons of the cockroach Periplaneta americana. The number, spatial distribution, and arrangement of axons and dendrites of descending neurons of cockroach Leucophaea maderae, Gromphadorhina portentosa, Blaberus craniifer, Nauphoeta cinerea (Blaberidae) were found to be similar. Neurons homologous to the ocellar, mechanosensory, and visual descending neurons described in the cockroach Periplaneta americana were found. It is suggested that during the evolution of the cockroach species, the adaptive behavior at danger was changed by transforming sensory inputs and motor responses, while the system of descending neurons remains stable.