Virtual Fly Brain-An interactive atlas of the Drosophila nervous system

Toward Principles of Brain Network Organization and Function

The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of behaviors. Understanding patterns of these complex interactions and how they are coordinated to support collective neural function is critical for parsing human and animal behavior, treating mental illness, and developing artificial intelligence. Rapid experimental advances in imaging, recording, and perturbing neural systems across various species now provide opportunities to distill underlying principles of brain organization and function. Here, we take stock of recent progress and review methods used in the statistical analysis of brain networks, drawing from fields of statistical physics, network theory, and information theory. Our discussion is organized by scale, starting with models of individual neurons and extending to large-scale networks mapped across brain regions. We then examine organizing principles and constraints that shape the biological structure and function of neural circuits. We conclude with an overview of several critical frontiers, including expanding current models, fostering tighter feedback between theory and experiment, and leveraging perturbative approaches to understand neural systems. Alongside these efforts, we highlight the importance of contextualizing their contributions by linking them to formal accounts of explanation and causation.

Comparative connectomics of Drosophila descending and ascending neurons

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and an information bottleneck connecting the brain and the ventral nerve cord (an analogue of the spinal cord) and comprises diverse populations of descending neurons (DNs), ascending neurons (ANs) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Here, by integrating three separate electron microscopy (EM) datasets1-4, we provide a complete connectomic description of the ANs and DNs of the Drosophila female nervous system and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions are matched across hemispheres, datasets and sexes. Crucially, we also match 51% of DN cell types to light-level data5 defining specific driver lines, as well as classifying all ascending populations. We use these results to reveal the anatomical and circuit logic of neck connective neurons. We observe connected chains of DNs and ANs spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analyses of selected circuits for reproductive behaviours, including male courtship6 (DNa12; also known as aSP22) and song production7 (AN neurons from hemilineage 08B) and female ovipositor extrusion8 (DNp13). Our work provides EM-level circuit analyses that span the entire central nervous system of an adult animal.

Olfactory projection neuron rewiring in the brain of an ecological specialist

Animal behaviors can differ greatly between closely related species. These behavioral changes are frequently linked to sensory system modifications, but central brain cell-type alterations might also be involved. Here, we develop advanced genetic tools to compare homologous central neurons in Drosophila sechellia, an ecological specialist, with the generalist Drosophila melanogaster. Through systematic morphological analysis of olfactory projection neurons (PNs), we reveal that the global anatomy of these second-order neurons is conserved. However, high-resolution, quantitative comparisons identify a striking case of convergent rewiring of PNs in two olfactory pathways critical for D. sechellia's host location. Calcium imaging and labeling of pre-synaptic sites in these evolved D. sechellia PNs indicate that species-specific connections with third-order partners are formed. This work demonstrates that peripheral sensory evolution is accompanied by selective wiring changes in the central brain to facilitate ecological specialization and paves the way to compare other cell types throughout the nervous system.

Differential neuronal vulnerability to C9orf72 repeat expansion driven by Xbp1-induced endoplasmic reticulum-associated degradation

Neurodegenerative diseases are characterized by the localized loss of neurons. Why cell death is triggered only in specific neuronal populations and whether it is the response to toxic insults or the initial cellular state that determines their vulnerability is unknown. To understand individual cell responses to disease, we profiled their transcriptional signatures throughout disease development in a Drosophila model of C9orf72 (G4C2) repeat expansion (C9), the most common genetic cause of frontotemporal dementia and amyotrophic lateral sclerosis. We identified neuronal populations specifically vulnerable or resistant to C9 expression and found an upregulation of protein homeostasis pathways in resistant neurons at baseline. Overexpression of Xbp1s, a key regulator of the unfolded protein response and a central node in the resistance network, rescues C9 toxicity. This study shows that neuronal vulnerability depends on the intrinsic transcriptional state of neurons and that leveraging resistant neurons' properties can boost resistance in vulnerable neurons.

A general strategy for generating expert-guided, simplified views of ontologies

Annotation with widely used, well-structured ontologies, combined with the use of ontology-aware software tools, ensures data and analyses are Findable, Accessible, Interoperable and Reusable (FAIR). Standardized terms with synonyms support lexical search. Ontology structure supports biologically meaningful grouping of annotations (typically by location and type). However, there are significant barriers to the adoption and use of ontologies by researchers and resource developers. One barrier is complexity. Ontologies serving diverse communities are often more complex than needed for individual applications. It is common for atlases to attempt their own simplifications by manually constructing hierarchies of terms linked to ontologies, but these typically include relationship types that are not suitable for grouping annotations. Here, we present a suite of tools for validating user hierarchies against ontology structure, using them to generate graphical reports for discussion and ontology views tailored to the needs of the HuBMAP Human Reference Atlas, and the Human Developmental Cell Atlas. In both cases, validation is a source of corrections and content for both ontologies and user hierarchies.

Convergent olfactory circuits for courtship in Drosophila revealed by ds-Tango

Animals exhibit sex-specific behaviors that are governed by sexually dimorphic circuits. One such behavior in male Drosophila melanogaster, courtship, is regulated by various sensory modalities, including olfaction. Here, we reveal how sexually dimorphic olfactory pathways in male flies converge at the third-order, onto lateral horn output neurons, to regulate courtship. To achieve this, we developed ds-Tango, a modified version of the monosynaptic tracing and manipulation tool trans-Tango. In ds-Tango, two distinct configurations of trans-Tango are positioned in series, thus providing selective genetic access not only to the monosynaptic partners of starter neurons but also to their disynaptic connections. Using ds-Tango, we identified a node of convergence for three sexually dimorphic olfactory pathways. Silencing this node results in deficits in sex recognition of potential partners. Our results identify lateral horn output neurons required for proper courtship behavior in male flies and establish ds-Tango as a tool for disynaptic circuit tracing.

Whole-brain annotation and multi-connectome cell typing of Drosophila

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

Exploring the Asymmetric Body's Influence on Interval Timing Behaviors of Drosophila melanogaster

The roles of brain asymmetry in Drosophila are diverse, encompassing the regulation of behavior, the creation of memory, neurodevelopment, and evolution. A comprehensive examination of the Drosophila brain has the potential to enhance our understanding of the functional significance of brain asymmetry in cognitive and behavioral processes, as well as its role in evolutionary perspectives. This study explores the influence of brain asymmetry on interval timing behaviors in Drosophila, with a specific focus on the asymmetric body (AB) structure. Despite being bilaterally symmetric, the AB exhibits functional asymmetry and is located within the central complex of the fly brain. Interval timing behaviors, such as rival-induced prolonged mating duration: longer mating duration behavior (LMD) and sexual experience-mediated shorter mating duration behavior (SMD), are essential for Drosophila. We utilize genetic manipulations to selectively activate or inhibit AB neurons and evaluates their impact on LMD and SMD behaviors. The results indicate that specific populations of AB neurons play unique roles in orchestrating these interval timing behaviors. Notably, inhibiting GAL4R38D01-labeled AB neurons disrupts both LMD and SMD, while GAL4R42C09 neuron inhibition affects only LMD. Moreover, hyperexcitation of GAL4R72A10-labeled AB neurons perturbs SMD. Our study identifies NetrinB (NetB) and Abdominal-B (Abd-B) are important genes for AB neurons in LMD and highlights the role of 5-HT1B neurons in generating LMD through peptidergic Pigment-dispersing factor (PDF) signaling. In summary, this study underscores the importance of AB neuron asymmetry in mediating interval timing behaviors and provides insights into the underlying mechanisms of memory formation and function in Drosophila.

The NFκB Dif is required for behavioral and molecular correlates of sleep homeostasis in Drosophila

The nuclear factor binding the κ light chain in B-cells (NFκB) is involved in a wide range of cellular processes including development, growth, innate immunity, and sleep. However, genetic studies of the role of specific NFκB transcription factors in sleep have been limited. Drosophila fruit flies carry three genes encoding NFκB transcription factors, Dorsal, Dorsal Immunity Factor (Dif), and Relish. We previously found that loss of the Relish gene from fat body suppressed daily nighttime sleep, and abolished infection-induced sleep. Here we show that Dif regulates daily sleep and recovery sleep following prolonged wakefulness. Mutants of Dif showed reduced daily sleep and suppressed recovery in response to sleep deprivation. Pan-neuronal knockdown of Dif strongly suppressed daily sleep, indicating that in contrast to Relish, Dif functions from the central nervous system to regulate sleep. Based on the unique expression pattern of a Dif- GAL4 driver, we hypothesized that its effects on sleep were mediated by the pars intercerebralis (PI). While RNAi knock-down of Dif in the PI reduced daily sleep, it had no effect on the recovery response to sleep deprivation. However, recovery sleep was suppressed when RNAi knock-down of Dif was distributed across a wider range of neurons. Induction of the nemuri (nur) antimicrobial peptide by sleep deprivation was reduced in Dif mutants and pan-neuronal overexpression of nur also suppressed the Dif mutant phenotype by significantly increasing sleep and reducing nighttime arousability. Together, these findings indicate that Dif functions from brain to target nemuri and to promote deep sleep.

LYNSU: automated 3D neuropil segmentation of fluorescent images for Drosophila brains

The brain atlas, which provides information about the distribution of genes, proteins, neurons, or anatomical regions, plays a crucial role in contemporary neuroscience research. To analyze the spatial distribution of those substances based on images from different brain samples, we often need to warp and register individual brain images to a standard brain template. However, the process of warping and registration may lead to spatial errors, thereby severely reducing the accuracy of the analysis. To address this issue, we develop an automated method for segmenting neuropils in the Drosophila brain for fluorescence images from the FlyCircuit database. This technique allows future brain atlas studies to be conducted accurately at the individual level without warping and aligning to a standard brain template. Our method, LYNSU (Locating by YOLO and Segmenting by U-Net), consists of two stages. In the first stage, we use the YOLOv7 model to quickly locate neuropils and rapidly extract small-scale 3D images as input for the second stage model. This stage achieves a 99.4% accuracy rate in neuropil localization. In the second stage, we employ the 3D U-Net model to segment neuropils. LYNSU can achieve high accuracy in segmentation using a small training set consisting of images from merely 16 brains. We demonstrate LYNSU on six distinct neuropils or structures, achieving a high segmentation accuracy comparable to professional manual annotations with a 3D Intersection-over-Union (IoU) reaching up to 0.869. Our method takes only about 7 s to segment a neuropil while achieving a similar level of performance as the human annotators. To demonstrate a use case of LYNSU, we applied it to all female Drosophila brains from the FlyCircuit database to investigate the asymmetry of the mushroom bodies (MBs), the learning center of fruit flies. We used LYNSU to segment bilateral MBs and compare the volumes between left and right for each individual. Notably, of 8,703 valid brain samples, 10.14% showed bilateral volume differences that exceeded 10%. The study demonstrated the potential of the proposed method in high-throughput anatomical analysis and connectomics construction of the Drosophila brain.

Neural-circuit basis of song preference learning in fruit flies

As observed in human language learning and song learning in birds, the fruit fly Drosophila melanogaster changes its auditory behaviors according to prior sound experiences. This phenomenon, known as song preference learning in flies, requires GABAergic input to pC1 neurons in the brain, with these neurons playing a key role in mating behavior. The neural circuit basis of this GABAergic input, however, is not known. Here, we find that GABAergic neurons expressing the sex-determination gene doublesex are necessary for song preference learning. In the brain, only four doublesex-expressing GABAergic neurons exist per hemibrain, identified as pCd-2 neurons. pCd-2 neurons directly, and in many cases mutually, connect with pC1 neurons, suggesting the existence of reciprocal circuits between them. Moreover, GABAergic and dopaminergic inputs to doublesex-expressing GABAergic neurons are necessary for song preference learning. Together, this study provides a neural circuit model that underlies experience-dependent auditory plasticity at a single-cell resolution.

Multiple isoforms of the Activin-like receptor baboon differentially regulate proliferation and conversion behaviors of neuroblasts and neuroepithelial cells in the Drosophila larval brain

In Drosophila coordinated proliferation of two neural stem cells, neuroblasts (NB) and neuroepithelial (NE) cells, is pivotal for proper larval brain growth that ultimately determines the final size and performance of an adult brain. The larval brain growth displays two phases based on behaviors of NB and NEs: the first one in early larval stages, influenced by nutritional status and the second one in the last larval stage, promoted by ecdysone signaling after critical weight checkpoint. Mutations of the baboon (babo) gene that produces three isoforms (BaboA-C), all acting as type-I receptors of Activin-type transforming growth factor β (TGF-β) signaling, cause a small brain phenotype due to severely reduced proliferation of the neural stem cells. In this study we show that loss of babo function severely affects proliferation of NBs and NEs as well as conversion of NEs from both phases. By analyzing babo-null and newly generated isoform-specific mutants by CRISPR mutagenesis as well as isoform-specific RNAi knockdowns in a cell- and stage-specific manner, our data support differential contributions of the isoforms for these cellular events with BaboA playing the major role. Stage-specific expression of EcR-B1 in the brain is also regulated primarily by BaboA along with function of the other isoforms. Blocking EcR function in both neural stem cells results in a small brain phenotype that is more severe than baboA-knockdown alone. In summary, our study proposes that the Babo-mediated signaling promotes proper behaviors of the neural stem cells in both phases and achieves this by acting upstream of EcR-B1 expression in the second phase.

Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

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.

Functional labeling of individualized postsynaptic neurons using optogenetics and trans-Tango in Drosophila (FLIPSOT)

A population of neurons interconnected by synapses constitutes a neural circuit, which performs specific functions upon activation. It is essential to identify both anatomical and functional entities of neural circuits to comprehend the components and processes necessary for healthy brain function and the changes that characterize brain disorders. To date, few methods are available to study these two aspects of a neural circuit simultaneously. In this study, we developed FLIPSOT, or functional labeling of individualized postsynaptic neurons using optogenetics and trans-Tango. FLIPSOT uses (1) trans-Tango to access postsynaptic neurons genetically, (2) optogenetic approaches to activate (FLIPSOTa) or inhibit (FLIPSOTi) postsynaptic neurons in a random and sparse manner, and (3) fluorescence markers tagged with optogenetic genes to visualize these neurons. Therefore, FLIPSOT allows using a presynaptic driver to identify the behavioral function of individual postsynaptic neurons. It is readily applied to identify functions of individual postsynaptic neurons and has the potential to be adapted for use in mammalian circuits.

Brain size scaling through development in the whitelined sphinx moth (Hyles lineata) shows mass and cell number comparable to flies, bees, and wasps

Factors regulating larval growth and determinants of adult body size are described for several holometabolous insects, but less is known about brain size scaling through development. Here we use the isotropic fractionation ("brain soup") method to estimate the number of brain cells and cell density for the whitelined sphinx moth (Lepidoptera: Hyles lineata) from the first instar through the adult stage. We measure mass and brain cell number and find that, during the larval stages, body mass shows an exponential relationship with head width, while the total number of brain cells increases asymptotically. Larval brain cell number increases by a factor of ten from nearly 8000 in the first instar to over 80,000 in the fifth instar. Brain cell number increases by another factor of 10 during metamorphosis, with the adult brain containing more than 900,000 cells. This is similar to increases during development in the vinegar fly (Drosophila melanogaster) and the black soldier fly (Hermetia illucens). The adult brain falls slightly below the brain-to-body allometry for wasps and bees but is comparable in the number of cells per unit brain mass, indicating a general conservation of brain cell density across these divergent lineages.

mtFRC: depth-dependent resolution quantification of image features in 3D fluorescence microscopy

Motivation

Quantifying lateral resolution as a function of depth is important in the design of 3D microscopy experiments. However, for many specimens, resolution is non-uniform within the same optical plane because of factors such as tissue variability and differential light scattering. This precludes application of a simple resolution metric to the image as a whole. In such cases, it can be desirable to analyse resolution only within specific, well-defined features.

Results

An algorithm and software are presented to characterize resolution as a function of depth in features of arbitrary shape in 3D samples. The tool can be used to achieve an objective comparison between different preparation methods, imaging parameters, and optical systems. It can also inform the design of experiments requiring resolution of structures at a specific scale. The method is demonstrated by quantifying the improvement in resolution of two-photon microscopy over confocal in the central brain of Drosophila melanogaster. Measurement of image quality increases by tuning a single parameter, laser power, is also shown. An ImageJ plugin implementation is provided for ease of use via a simple Graphical User Interface, with outputs in table, graph, and colourmap formats.

Availability and implementation

Software and source code are available at https://www.imperial.ac.uk/rowlands-lab/resources/.

Semantic representation of neural circuit knowledge in Caenorhabditis elegans

In modern biology, new knowledge is generated quickly, making it challenging for researchers to efficiently acquire and synthesise new information from the large volume of primary publications. To address this problem, computational approaches that generate machine-readable representations of scientific findings in the form of knowledge graphs have been developed. These representations can integrate different types of experimental data from multiple papers and biological knowledge bases in a unifying data model, providing a complementary method to manual review for interacting with published knowledge. The Gene Ontology Consortium (GOC) has created a semantic modelling framework that extends individual functional gene annotations to structured descriptions of causal networks representing biological processes (Gene Ontology-Causal Activity Modelling, or GO-CAM). In this study, we explored whether the GO-CAM framework could represent knowledge of the causal relationships between environmental inputs, neural circuits and behavior in the model nematode C. elegans [C. elegans Neural-Circuit Causal Activity Modelling (CeN-CAM)]. We found that, given extensions to several relevant ontologies, a wide variety of author statements from the literature about the neural circuit basis of egg-laying and carbon dioxide (CO2) avoidance behaviors could be faithfully represented with CeN-CAM. Through this process, we were able to generate generic data models for several categories of experimental results. We also discuss how semantic modelling may be used to functionally annotate the C. elegans connectome. Thus, Gene Ontology-based semantic modelling has the potential to support various machine-readable representations of neurobiological knowledge.

Dopamine-Dependent Plasticity Is Heterogeneously Expressed by Presynaptic Calcium Activity across Individual Boutons of the Drosophila Mushroom Body

The Drosophila mushroom body (MB) is an important model system for studying the synaptic mechanisms of associative learning. In this system, coincidence of odor-evoked calcium influx and dopaminergic input in the presynaptic terminals of Kenyon cells (KCs), the principal neurons of the MB, triggers long-term depression (LTD), which plays a critical role in olfactory learning. However, it is controversial whether such synaptic plasticity is accompanied by a corresponding decrease in odor-evoked calcium activity in the KC presynaptic terminals. Here, we address this question by inducing LTD by pairing odor presentation with optogenetic activation of dopaminergic neurons (DANs). This allows us to rigorously compare the changes at the presynaptic and postsynaptic sites in the same conditions. By imaging presynaptic acetylcholine release in the condition where LTD is reliably observed in the postsynaptic calcium signals, we show that neurotransmitter release from KCs is depressed selectively in the MB compartments innervated by activated DANs, demonstrating the presynaptic nature of LTD. However, total odor-evoked calcium activity of the KC axon bundles does not show concurrent depression. We further conduct calcium imaging in individual presynaptic boutons and uncover the highly heterogeneous nature of calcium plasticity. Namely, only a subset of boutons, which are strongly activated by associated odors, undergo calcium activity depression, while weakly responding boutons show potentiation. Thus, our results suggest an unexpected nonlinear relationship between presynaptic calcium influx and the results of plasticity, challenging the simple view of cooperative actions of presynaptic calcium and dopaminergic input.

Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila

The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.

Mushroom body output neurons MBON-a1/a2 define an odor intensity channel that regulates behavioral odor discrimination learning in larval Drosophila

The sensitivity of animals to sensory input must be regulated to ensure that signals are detected and also discriminable. However, how circuits regulate the dynamic range of sensitivity to sensory stimuli is not well understood. A given odor is represented in the insect mushroom bodies (MBs) by sparse combinatorial coding by Kenyon cells (KCs), forming an odor quality representation. To address how intensity of sensory stimuli is processed at the level of the MB input region, the calyx, we characterized a set of novel mushroom body output neurons that respond preferentially to high odor concentrations. We show that a pair of MB calyx output neurons, MBON-a1/2, are postsynaptic in the MB calyx, where they receive extensive synaptic inputs from KC dendrites, the inhibitory feedback neuron APL, and octopaminergic sVUM1 neurons, but relatively few inputs from projection neurons. This pattern is broadly consistent in the third-instar larva as well as in the first instar connectome. MBON-a1/a2 presynaptic terminals innervate a region immediately surrounding the MB medial lobe output region in the ipsilateral and contralateral brain hemispheres. By monitoring calcium activity using jRCamP1b, we find that MBON-a1/a2 responses are odor-concentration dependent, responding only to ethyl acetate (EA) concentrations higher than a 200-fold dilution, in contrast to MB neurons which are more concentration-invariant and respond to EA dilutions as low as 10^-4. Optogenetic activation of the calyx-innervating sVUM1 modulatory neurons originating in the SEZ (Subesophageal zone), did not show a detectable effect on MBON-a1/a2 odor responses. Optogenetic activation of MBON-a1/a2 using CsChrimson impaired odor discrimination learning compared to controls. We propose that MBON-a1/a2 form an output channel of the calyx, summing convergent sensory and modulatory input, firing preferentially to high odor concentration, and might affect the activity of downstream MB targets.

Neuromorphological Atlas of Human Prenatal Brain Development: White Paper

Recent morphological data on human brain development are quite fragmentary. However, they are highly requested for a number of medical practices, educational programs, and fundamental research in the fields of embryology, cytology and histology, neurology, physiology, path anatomy, neonatology, and others. This paper provides the initial information on the new online Human Prenatal Brain Development Atlas (HBDA). The Atlas will start with forebrain annotated hemisphere maps, based on human fetal brain serial sections at the different stages of prenatal ontogenesis. Spatiotemporal changes in the regional-specific immunophenotype profiles will also be demonstrated on virtual serial sections. The HBDA can serve as a reference database for the neurological research, which provides opportunity to compare the data obtained by noninvasive techniques, such as neurosonography, X-ray computed tomography and magnetic resonance imaging, functional magnetic resonance imaging, 3D high-resolution phase-contrast computed tomography visualization techniques, as well as spatial transcriptomics data. It could also become a database for the qualitative and quantitative analysis of individual variability in the human brain. Systemized data on the mechanisms and pathways of prenatal human glio- and neurogenesis could also contribute to the search for new therapy methods for a large spectrum of neurological pathologies, including neurodegenerative and cancer diseases. The preliminary data are now accessible on the special HBDA website.