Flybrain neuron database: a comprehensive database system of the Drosophila brain neurons

Bridging the Brain and Data Sciences

Brain scientists are now capable of collecting more data in a single experiment than researchers a generation ago might have collected over an entire career. Indeed, the brain itself seems to thirst for more and more data. Such digital information not only comprises individual studies but is also increasingly shared and made openly available for secondary, confirmatory, and/or combined analyses. Numerous web resources now exist containing data across spatiotemporal scales. Data processing workflow technologies running via cloud-enabled computing infrastructures allow for large-scale processing. Such a move toward greater openness is fundamentally changing how brain science results are communicated and linked to available raw data and processed results. Ethical, professional, and motivational issues challenge the whole-scale commitment to data-driven neuroscience. Nevertheless, fueled by government investments into primary brain data collection coupled with increased sharing and community pressure challenging the dominant publishing model, large-scale brain and data science is here to stay.

Identification of Neuronal Polarity by Node-Based Machine Learning

Identifying the direction of signal flows in neural networks is important for understanding the intricate information dynamics of a living brain. Using a dataset of 213 projection neurons distributed in more than 15 neuropils of a Drosophila brain, we develop a powerful machine learning algorithm: node-based polarity identifier of neurons (NPIN). The proposed model is trained only by information specific to nodes, the branch points on the skeleton, and includes both Soma Features (which contain spatial information from a given node to a soma) and Local Features (which contain morphological information of a given node). After including the spatial correlations between nodal polarities, our NPIN provided extremely high accuracy (>96.0%) for the classification of neuronal polarity, even for complex neurons with more than two dendrite/axon clusters. Finally, we further apply NPIN to classify the neuronal polarity of neurons in other species (Blowfly and Moth), which have much less neuronal data available. Our results demonstrate the potential of NPIN as a powerful tool to identify the neuronal polarity of insects and to map out the signal flows in the brain’s neural networks if more training data become available in the future.

A connectome and analysis of the adult Drosophila central brain

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.

The Fly Brain Atlas

The brain's synaptic networks endow an animal with powerfully adaptive biological behavior. Maps of such synaptic circuits densely reconstructed in those model brains that can be examined and manipulated by genetic means offer the best prospect for understanding the underlying biological bases of behavior. That prospect is now technologically feasible and a scientifically enabling possibility in neurobiology, much as genomics has been in molecular biology and genetics. In Drosophila, two major advances are in electron microscopic technology, using focused ion beam-scanning electron microscopy (FIB-SEM) milling to capture and align digital images, and in computer-aided reconstruction of neuron morphologies. The last decade has witnessed enormous progress in detailed knowledge of the actual synaptic circuits formed by real neurons. Advances in various brain regions that heralded identification of the motion-sensing circuits in the optic lobe are now extending to other brain regions, with the prospect of encompassing the fly's entire nervous system, both brain and ventral nerve cord.

Working Memory: It's a Gas, Gas, Gas

The ellipsoid body, a doughnut-shaped part of the fly brain, is essential for visual working memory. Gaseous second messengers establish a functional ellipsoid body and act as a short-term aid in orientation behavior.

A Single-Cell Level and Connectome-Derived Computational Model of the Drosophila Brain

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which (1) identifies the polarity of each neuron arbor, (2) predicts connections between neurons, (3) translates morphology data from the database into physiology parameters for computational modeling, (4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and (5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

Neuronal, mathematical, and molecular bases of perceptual decision-making in C. elegans

Animals process sensory information from the environment to make behavioral decisions. Although environmental information may be ambiguous or gradually changing, animals can still choose one behavioral option among several through perceptual decision-making. Perceptual decision-making has been intensively studied in primates and rodents, and neural activity that accumulates sensory information has been shown to be crucial. However, it remains unclear how the accumulating neural activity is generated, and whether such activity is a conserved decision-making strategy across the animal kingdom. Here, we review the previous perceptual decision-making studies in vertebrates and invertebrates and our recent achievement in an invertebrate model animal, the nematode Caenorhabditis elegans. In the study, we analyzed temporal dynamics of neuronal activity during perceptual decision-making in navigational behavior of C. elegans. We identified neural activity that accumulates sensory information and elucidated the molecular mechanism for the accumulating activity, which may be relevant to decision-making across the animal kingdom.

The world of the identified or digital neuron

In general, neurons in insects and many other invertebrate groups are individually recognizable, enabling us to assign an index number to specific neurons in a manner which is rarely possible in a vertebrate brain. This endows many studies on insect nervous systems with the opportunity to document neurons with great precision, so that in favourable cases we can return to the same neuron or neuron type repeatedly so as to recognize many separate morphological classes. The visual system of the fly's compound eye particularly provides clear examples of the accuracy of neuron wiring, allowing numerical comparisons between representatives of the same cell type, and estimates of the accuracy of their wiring.

Toward Whole-Body Connectomics

Recent advances in neuro-technologies have revolutionized knowledge of brain structure and functions. Governments and private organizations worldwide have initiated several large-scale brain connectome projects, to further understand how the brain works at the systems levels. Most recent projects focus on only brain neurons, with the exception of an early effort to reconstruct the 302 neurons that comprise the whole body of the small worm, Caenorhabditis elegans However, to fully elucidate the neural circuitry of complex behavior, it is crucial to understand brain interactions with the whole body, which can be achieved only by mapping the whole-body connectome. In this article, we discuss the current state of connectomics study, focusing on novel optical approaches and related imaging technologies. We also discuss the challenges encountered by scientists who endeavor to map these whole-body connectomes in large animals.

The role of the Drosophila lateral horn in olfactory information processing and behavioral response

Animals must rapidly and accurately process environmental information to produce the correct behavioral responses. Reactions to previously encountered as well as to novel but biologically important stimuli are equally important, and one understudied region in the insect brain plays a role in processing both types of stimuli. The lateral horn is a higher order processing center that mainly processes olfactory information and is linked via olfactory projection neurons to another higher order learning center, the mushroom body. This review focuses on the lateral horn of Drosophila where most functional studies have been performed. We discuss connectivity between the primary olfactory center, the antennal lobe, and the lateral horn and mushroom body. We also present evidence for the lateral horn playing roles in innate behavioral responses by encoding biological valence to novel odor cues and in learned responses to previously encountered odors by modulating neural activity within the mushroom body. We describe how these processes contribute to acceptance or avoidance of appropriate or inappropriate mates and food, as well as the identification of predators. The lateral horn is a sexually dimorphic and plastic region of the brain that modulates other regions of the brain to ensure that insects produce rapid and effective behavioral responses to both novel and learned stimuli, yet multiple gaps exist in our knowledge of this important center. We anticipate that future studies on olfactory processing, learning, and innate behavioral responses will include the lateral horn in their examinations, leading to a more comprehensive understanding of olfactory information relay and resulting behaviors.

Fine structure of synaptic sites and circuits in mushroom bodies of insect brains

In the insect brain, mushroom bodies represent a prominent central neuropil for multisensory integration and, crucially, for learning and memory. For this reason, special attention has been focused on its small chemical synapses. Early studies on synaptic types and their distribution, using conventional electron microscopy, and recent publications have resolved basic features of synaptic circuits. More recent studies, using experimental methods for resolving neurons, such as immunocytochemistry, genetic labelling, high resolution confocal microscopy and more advanced electron microscopy, have revealed many new details about the fine structure and molecular contents of identifiable neurons of mushroom bodies and has led to more refined modelling of functional organisation. Synaptic circuitries have been described in most detail for the calyces. In contrast, the mushroom bodies' columnar peduncle and lobes have been explored to a lesser degree. In dissecting local microcircuits, the scientist is confronted with complex neuronal compartmentalisation and specific synaptic arrangements. This article reviews classical and modern studies on the fine structure of synapses and their networks in mushroom bodies across several insect species.

Synaptic circuitry of identified neurons in the antennal lobe of Drosophila melanogaster

In Drosophila melanogaster olfactory sensory neurons (OSNs) establish synapses with projection neurons (PNs) and local interneurons within antennal lobe (AL) glomeruli. Substantial knowledge regarding this circuitry has been obtained by functional studies, whereas ultrastructural evidence of synaptic contacts is scarce. To fill this gap, we studied serial sections of three glomeruli using electron microscopy. Ectopic expression of a membrane-bound peroxidase allowed us to map synaptic sites along PN dendrites. Our data prove for the first time that each of the three major types of AL neurons is both pre- and postsynaptic to the other two types, as previously indicated by functional studies. PN dendrites carry a large proportion of output synapses, with approximately one output per every three input synapses. Detailed reconstructions of PN dendrites showed that these synapses are distributed unevenly, with input and output sites partially segregated along a proximal-distal gradient and the thinnest branches carrying solely input synapses. Moreover, our data indicate synapse clustering, as we found evidence of dendritic tiling of PN dendrites. PN output synapses exhibited T-shaped presynaptic densities, mostly arranged as tetrads. In contrast, output synapses from putative OSNs showed elongated presynaptic densities in which the T-bar platform was supported by several pedestals and contacted as many as 20 postsynaptic profiles. We also discovered synaptic contacts between the putative OSNs. The average synaptic density in the glomerular neuropil was about two synapses/µm(3) . These results are discussed with regard to current models of olfactory glomerular microcircuits across species.

A subset of neurons controls the permeability of the peritrophic matrix and midgut structure in Drosophila adults

The metazoan gut performs multiple physiological functions, including digestion and absorption of nutrients, and also serves as a physical and chemical barrier against ingested pathogens and abrasive particles. Maintenance of these functions and structures is partly controlled by the nervous system, yet the precise roles and mechanisms of the neural control of gut integrity remain to be clarified in Drosophila Here, we screened for GAL4 enhancer-trap strains and labeled a specific subsets of neurons, using Kir2.1 to inhibit their activity. We identified an NP3253 line that is susceptible to oral infection by Gram-negative bacteria. The subset of neurons driven by the NP3253 line includes some of the enteric neurons innervating the anterior midgut, and these flies have a disorganized proventricular structure with high permeability of the peritrophic matrix and epithelial barrier. The findings of the present study indicate that neural control is crucial for maintaining the barrier function of the gut, and provide a route for genetic dissection of the complex brain-gut axis in adults of the model organism Drosophila.

Automated in situ brain imaging for mapping the Drosophila connectome

Mapping the connectome, a wiring diagram of the entire brain, requires large-scale imaging of numerous single neurons with diverse morphology. It is a formidable challenge to reassemble these neurons into a virtual brain and correlate their structural networks with neuronal activities, which are measured in different experiments to analyze the informational flow in the brain. Here, we report an in situ brain imaging technique called Fly Head Array Slice Tomography (FHAST), which permits the reconstruction of structural and functional data to generate an integrative connectome in Drosophila. Using FHAST, the head capsules of an array of flies can be opened with a single vibratome sectioning to expose the brains, replacing the painstaking and inconsistent brain dissection process. FHAST can reveal in situ brain neuroanatomy with minimal distortion to neuronal morphology and maintain intact neuronal connections to peripheral sensory organs. Most importantly, it enables the automated 3D imaging of 100 intact fly brains in each experiment. The established head model with in situ brain neuroanatomy allows functional data to be accurately registered and associated with 3D images of single neurons. These integrative data can then be shared, searched, visualized, and analyzed for understanding how brain-wide activities in different neurons within the same circuit function together to control complex behaviors.

Mapping chromatic pathways in the Drosophila visual system

In Drosophila, color vision and wavelength-selective behaviors are mediated by the compound eye's narrow-spectrum photoreceptors R7 and R8 and their downstream medulla projection (Tm) neurons Tm5a, Tm5b, Tm5c, and Tm20 in the second optic neuropil or medulla. These chromatic Tm neurons project axons to a deeper optic neuropil, the lobula, which in insects has been implicated in processing and relaying color information to the central brain. The synaptic targets of the chromatic Tm neurons in the lobula are not known, however. Using a modified GFP reconstitution across synaptic partners (GRASP) method to probe connections between the chromatic Tm neurons and 28 known and novel types of lobula neurons, we identify anatomically the visual projection neurons LT11 and LC14 and the lobula intrinsic neurons Li3 and Li4 as synaptic targets of the chromatic Tm neurons. Single-cell GRASP analyses reveal that Li4 receives synaptic contacts from over 90% of all four types of chromatic Tm neurons, whereas LT11 is postsynaptic to the chromatic Tm neurons, with only modest selectivity and at a lower frequency and density. To visualize synaptic contacts at the ultrastructural level, we develop and apply a "two-tag" double-labeling method to label LT11's dendrites and the mitochondria in Tm5c's presynaptic terminals. Serial electron microscopic reconstruction confirms that LT11 receives direct contacts from Tm5c. This method would be generally applicable to map the connections of large complex neurons in Drosophila and other animals.

Parallel neural pathways in higher visual centers of the Drosophila brain that mediate wavelength-specific behavior

Compared with connections between the retinae and primary visual centers, relatively less is known in both mammals and insects about the functional segregation of neural pathways connecting primary and higher centers of the visual processing cascade. Here, using the Drosophila visual system as a model, we demonstrate two levels of parallel computation in the pathways that connect primary visual centers of the optic lobe to computational circuits embedded within deeper centers in the central brain. We show that a seemingly simple achromatic behavior, namely phototaxis, is under the control of several independent pathways, each of which is responsible for navigation towards unique wavelengths. Silencing just one pathway is enough to disturb phototaxis towards one characteristic monochromatic source, whereas phototactic behavior towards white light is not affected. The response spectrum of each demonstrable pathway is different from that of individual photoreceptors, suggesting subtractive computations. A choice assay between two colors showed that these pathways are responsible for navigation towards, but not for the detection itself of, the monochromatic light. The present study provides novel insights about how visual information is separated and processed in parallel to achieve robust control of an innate behavior.

Controlling feeding behavior by chemical or gene-directed targeting in the brain: what's so spatial about our methods?

Intracranial chemical injection (ICI) methods have been used to identify the locations in the brain where feeding behavior can be controlled acutely. Scientists conducting ICI studies often document their injection site locations, thereby leaving kernels of valuable location data for others to use to further characterize feeding control circuits. Unfortunately, this rich dataset has not yet been formally contextualized with other published neuroanatomical data. In particular, axonal tracing studies have delineated several neural circuits originating in the same areas where ICI injection feeding-control sites have been documented, but it remains unclear whether these circuits participate in feeding control. Comparing injection sites with other types of location data would require careful anatomical registration between the datasets. Here, a conceptual framework is presented for how such anatomical registration efforts can be performed. For example, by using a simple atlas alignment tool, a hypothalamic locus sensitive to the orexigenic effects of neuropeptide Y (NPY) can be aligned accurately with the locations of neurons labeled by anterograde tracers or those known to express NPY receptors or feeding-related peptides. This approach can also be applied to those intracranial "gene-directed" injection (IGI) methods (e.g., site-specific recombinase methods, RNA expression or interference, optogenetics, and pharmacosynthetics) that involve viral injections to targeted neuronal populations. Spatial alignment efforts can be accelerated if location data from ICI/IGI methods are mapped to stereotaxic brain atlases to allow powerful neuroinformatics tools to overlay different types of data in the same reference space. Atlas-based mapping will be critical for community-based sharing of location data for feeding control circuits, and will accelerate our understanding of structure-function relationships in the brain for mammalian models of obesity and metabolic disorders.

Organization of antennal lobe-associated neurons in adult Drosophila melanogaster brain

The primary olfactory centers of both vertebrates and insects are characterized by glomerular structure. Each glomerulus receives sensory input from a specific type of olfactory sensory neurons, creating a topographic map of the odor quality. The primary olfactory center is also innervated by various types of neurons such as local neurons, output projection neurons (PNs), and centrifugal neurons from higher brain regions. Although recent studies have revealed how olfactory sensory input is conveyed to each glomerulus, it still remains unclear how the information is integrated and conveyed to other brain areas. By using the GAL4 enhancer-trap system, we conducted a systematic mapping of the neurons associated with the primary olfactory center of Drosophila, the antennal lobe (AL). We identified in total 29 types of neurons, among which 13 are newly identified in the present study. Analyses of arborizations of these neurons in the AL revealed how glomeruli are linked with each other, how different PNs link these glomeruli with multiple secondary sites, and how these secondary sites are organized by the projections of the AL-associated neurons.

Identification of a dopamine pathway that regulates sleep and arousal in Drosophila

Sleep is required to maintain physiological functions, including memory, and is regulated by monoamines across species. Enhancement of dopamine signals by a mutation in the dopamine transporter (DAT) decreases sleep, but the underlying dopamine circuit responsible for this remains unknown. We found that the D1 dopamine receptor (DA1) in the dorsal fan-shaped body (dFSB) mediates the arousal effect of dopamine in Drosophila. The short sleep phenotype of the DAT mutant was completely rescued by an additional mutation in the DA1 (also known as DopR) gene, but expression of wild-type DA1 in the dFSB restored the short sleep phenotype. We found anatomical and physiological connections between dopamine neurons and the dFSB neuron. Finally, we used mosaic analysis with a repressive marker and found that a single dopamine neuron projecting to the FSB activated arousal. These results suggest that a local dopamine pathway regulates sleep.

A strategy for building neuroanatomy ontologies

MOTIVATION

Advancing our understanding of how nervous systems work will require the ability to store and annotate 3D anatomical datasets, recording morphology, partonomy and connectivity at multiple levels of granularity from subcellular to gross anatomy. It will also require the ability to integrate this data with other data-types including functional, genetic and electrophysiological data. The web ontology language OWL2 provides the means to solve many of these problems. Using it, one can rigorously define and relate classes of anatomical structure using multiple criteria. The resulting classes can be used to annotate datasets recording, for example, gene expression or electrophysiology. Reasoning software can be used to automate classification and error checking and to construct and answer sophisticated combinatorial queries. But for such queries to give consistent and biologically meaningful results, it is important that both classes and the terms (relations) used to relate them are carefully defined.

RESULTS

We formally define a set of relations for recording the spatial and connectivity relationships of neuron classes and brain regions in a broad range of species, from vertebrates to arthropods. We illustrate the utility of our approach via its application in the ontology that drives the Virtual Fly Brain web resource.

AVAILABILITY AND IMPLEMENTATION

The relations we define are available from http://purl.obolibrary.org/obo/ro.owl. They are used in the Drosophila anatomy ontology (http://purl.obolibrary.org/obo/fbbt/2011-09-06/), which drives the web resource http://www.virtualflybrain.org

Auditory circuit in the Drosophila brain

Most animals exhibit innate auditory behaviors driven by genetically hardwired neural circuits. In Drosophila, acoustic information is relayed by Johnston organ neurons from the antenna to the antennal mechanosensory and motor center (AMMC) in the brain. Here, by using structural connectivity analysis, we identified five distinct types of auditory projection neurons (PNs) interconnecting the AMMC, inferior ventrolateral protocerebrum (IVLP), and ventrolateral protocerebrum (VLP) regions of the central brain. These auditory PNs are also functionally distinct; AMMC-B1a, AMMC-B1b, and AMMC-A2 neurons differ in their responses to sound (i.e., they are narrowly tuned or broadly tuned); one type of audioresponsive IVLP commissural PN connecting the two hemispheres is GABAergic; and one type of IVLP-VLP PN acts as a generalist responding to all tested audio frequencies. Our findings delineate an auditory processing pathway involving AMMC→IVLP→VLP in the Drosophila brain.

The genetic analysis of functional connectomics in Drosophila

Fly and vertebrate nervous systems share many organizational features, such as layers, columns and glomeruli, and utilize similar synaptic components, such as ion channels and receptors. Both also exhibit similar network features. Recent technological advances, especially in electron microscopy, now allow us to determine synaptic circuits and identify pathways cell-by-cell, as part of the fly's connectome. Genetic tools provide the means to identify synaptic components, as well as to record and manipulate neuronal activity, adding function to the connectome. This review discusses technical advances in these emerging areas of functional connectomics, offering prognoses in each and identifying the challenges in bridging structural connectomics to molecular biology and synaptic physiology, thereby determining fundamental mechanisms of neural computation that underlie behavior.