A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster

Studying complex brain dynamics using Drosophila

The field has successfully used Drosophila genetic tools to identify neurons and sub-circuits important for specific functions. However, for an organism with complex and changing internal states to succeed in a complex and changing natural environment, many neurons and circuits need to interact dynamically. Drosophila's many advantages, combined with new imaging tools, offer unique opportunities to study how the brain functions as a complex dynamical system. We give an overview of complex activity patterns and how they can be observed, as well as modeling strategies, adding proof of principle in some cases.

The case for emulating insect brains using anatomical "wiring diagrams" equipped with biophysical models of neuronal activity

Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). More specifically, this would entail creating biologically realistic simulations of entire insect nervous systems along with more approximate simulations of non-neuronal insect physiology to make "virtual insects." I argue that this could be realistically achievable within the next 20 years. I propose that developing emulations of insect brains will galvanize the global community of scientists, businesspeople, and policymakers toward pursuing the loftier goal of emulating the human brain. By demonstrating that WBE is possible via IBE, simulating mammalian brains and eventually the human brain may no longer be viewed as too radically ambitious to deserve substantial funding and resources. Furthermore, IBE will facilitate dramatic advances in cognitive neuroscience, artificial intelligence, and robotics through studies performed using virtual insects.

The fight to understand fighting: neurogenetic approaches to the study of aggression in insects

Aggression is an evolutionarily conserved behavior that evolved in the framework of defending or obtaining resources. When expressed out of context, unchecked aggression can have destructive consequences. Model systems that allow examination of distinct neuronal networks at the molecular, cellular, and circuit levels are adding immensely to our understanding of the biological basis of this behavior and should be relatable to other species up to and including man. Investigators have made particular use of insect models to both describe this quantifiable and stereotyped behavior and to manipulate genes and neuron function via numerous genetic and pharmacological tools. This review discusses recent advances in techniques that improve our ability to identify, manipulate, visualize, and compare the genes, neurons, and circuits that are required for the output of this complex and clinically relevant social behavior.

Neuronal mechanisms underlying innate and learned olfactory processing in Drosophila

Olfaction allows animals to adapt their behavior in response to different chemical cues in their environment. How does the brain efficiently discriminate different odors to drive appropriate behavior, and how does it flexibly assign value to odors to adjust behavior according to experience? This review traces neuronal mechanisms underlying these processes in adult Drosophila melanogaster from olfactory receptors to higher brain centers. We highlight neural circuit principles such as lateral inhibition, segregation and integration of olfactory channels, temporal accumulation of sensory evidence, and compartmentalized synaptic plasticity underlying associative memory.

The prandial process in flies

Feeding is fundamental to any heterotroph organism; in its role to quell hunger it overrides most other motivational states. But feeding also literally opens the door to harmful risks, especially for a saprophagous animal like Drosophila; ingestion of poisonous substrate can lead to irreversible damage. Thus feeding incorporates a series of steps with several checkpoints to guarantee that the ingestion remains beneficial and provides a balanced diet, or the feeding process is interrupted. Subsequently, we will summarize and describe the feeding process in Drosophila in a comprehensive manner. We propose eleven distinct steps for feeding, grouped into four categories, to address our current knowledge of prandial regulatory mechanisms in Drosophila.

Linking physiological processes and feeding behaviors by octopamine

The biogenic amine octopamine and to some extent its precursor tyramine function as an alerting signal in insects. Octopaminergic/tyraminergic neurons arborize in most parts of the central nervous system and additionally reach almost all peripheral organs, tissues, and muscles. Indeed, octopamine is involved in motivation, arousal, and the initiation of different behaviors reflecting its function as an alerting signal. A well-studied example of octopamine function is feeding behavior in Drosophila. Here, the amine is involved in food search, sugar/bitter sensitivity, food intake, and starvation-induced hyperactivity. Thereby octopamine modulates feeding initiation in response to internal needs and external stimuli. Additionally, it seems that octopamine/tyramine orchestrate behaviors such as locomotion and feeding or flight and song production to adapt the behavioral outcome of an animal to physiological and environmental conditions. There is a possibility that octopamine and tyramine are required in the selection of behaviors in insects.

Zebrafish Neuroscience: Using Artificial Neural Networks to Help Understand Brains

Brains are notoriously hard to understand, and neuroscientists need all the tools they can get their hands on to have a realistic shot at it. Advances in machine learning are proving instrumental, illustrated by their recent use to shed light on navigational strategies implemented by zebrafish brains.

Drosophila Neuroscience: Should I Land or Should I Jump?

Information about behavioral states can be integrated in decision-making circuits. In Drosophila, the behavioral state - flying versus not flying - determines whether flies land or jump by dynamically coupling visual information to pre-motor descending neurons.

The Organization of the Second Optic Chiasm of the Drosophila Optic Lobe

Visual pathways from the compound eye of an insect relay to four neuropils, successively the lamina, medulla, lobula, and lobula plate in the underlying optic lobe. Among these neuropils, the medulla, lobula, and lobula plate are interconnected by the complex second optic chiasm, through which the anteroposterior axis undergoes an inversion between the medulla and lobula. Given their complex structure, the projection patterns through the second optic chiasm have so far lacked critical analysis. By densely reconstructing axon trajectories using a volumetric scanning electron microscopy (SEM) technique, we reveal the three-dimensional structure of the second optic chiasm of Drosophila melanogaster, which comprises interleaving bundles and sheets of axons insulated from each other by glial sheaths. These axon bundles invert their horizontal sequence in passing between the medulla and lobula. Axons connecting the medulla and lobula plate are also bundled together with them but do not decussate the sequence of their horizontal positions. They interleave with sheets of projection neuron axons between the lobula and lobula plate, which also lack decussations. We estimate that approximately 19,500 cells per hemisphere, about two thirds of the optic lobe neurons, contribute to the second chiasm, most being Tm cells, with an estimated additional 2,780 T4 and T5 cells each. The chiasm mostly comprises axons and cell body fibers, but also a few synaptic elements. Based on our anatomical findings, we propose that a chiasmal structure between the neuropils is potentially advantageous for processing complex visual information in parallel. The EM reconstruction shows not only the structure of the chiasm in the adult brain, the previously unreported main topic of our study, but also suggest that the projection patterns of the neurons comprising the chiasm may be determined by the proliferation centers from which the neurons develop. Such a complex wiring pattern could, we suggest, only have arisen in several evolutionary steps.

An Adult Brain Atlas Reveals Broad Neuroanatomical Changes in Independently Evolved Populations of Mexican Cavefish

A shift in environmental conditions impacts the evolution of complex developmental and behavioral traits. The Mexican cavefish, Astyanax mexicanus, is a powerful model for examining the evolution of development, physiology, and behavior because multiple cavefish populations can be compared to an extant, ancestral-like surface population of the same species. Many behaviors have diverged in cave populations of A. mexicanus, and previous studies have shown that cavefish have a loss of sleep, reduced stress, an absence of social behaviors, and hyperphagia. Despite these findings, surprisingly little is known about the changes in neuroanatomy that underlie these behavioral phenotypes. Here, we use serial sectioning to generate brain atlases of surface fish and three independent cavefish populations. Volumetric reconstruction of serial-sectioned brains confirms convergent evolution on reduced optic tectum volume in all cavefish populations tested. In addition, we quantified volumes of specific neuroanatomical loci within several brain regions that have previously been implicated in behavioral regulation, including the hypothalamus, thalamus, and habenula. These analyses reveal an enlargement of the hypothalamus in all cavefish populations relative to surface fish, as well as subnuclei-specific differences within the thalamus and prethalamus. Taken together, these analyses support the notion that changes in environmental conditions are accompanied by neuroanatomical changes in brain structures associated with behavior. This atlas provides a resource for comparative neuroanatomy of additional brain regions and the opportunity to associate brain anatomy with evolved changes in behavior.

To court or not to court - a multimodal sensory decision in Drosophila males

When Drosophila males encounter another fly, they have to make a rapid assessment to ensure the appropriate response: should they court, fight or pursue a different action entirely? Previous work has focused on the significance of sensory cues detected by the male during these encounters; however, recent evidence highlights the importance of the male's own internal state in shaping his responses. Additionally, once triggered, courtship is not a rigid sequence of motor actions, but rather a finely tuned behavioural display that must continually update in response to sensory feedback. Here, we review recent findings highlighting how sensory information and internal states are integrated ensuring appropriate action selection, and how they sustain and fine-tune motor output. We further discuss recent advances in our understanding of species differences in sensory processing that may contribute to reproductive isolation.

3D cellular reconstruction of cortical glia and parenchymal morphometric analysis from Serial Block-Face Electron Microscopy of juvenile rat

With the rapid evolution in the automation of serial electron microscopy in life sciences, the acquisition of terabyte-sized datasets is becoming increasingly common. High resolution serial block-face imaging (SBEM) of biological tissues offers the opportunity to segment and reconstruct nanoscale structures to reveal spatial features previously inaccessible with simple, single section, two-dimensional images. In particular, we focussed here on glial cells, whose reconstruction efforts in literature are still limited, compared to neurons. We imaged a 750,000 cubic micron volume of the somatosensory cortex from a juvenile P14 rat, with 20 nm accuracy. We recognized a total of 186 cells using their nuclei, and classified them as neuronal or glial based on features of the soma and the processes. We reconstructed for the first time 4 almost complete astrocytes and neurons, 4 complete microglia and 4 complete pericytes, including their intracellular mitochondria, 186 nuclei and 213 myelinated axons. We then performed quantitative analysis on the three-dimensional models. Out of the data that we generated, we observed that neurons have larger nuclei, which correlated with their lesser density, and that astrocytes and pericytes have a higher surface to volume ratio, compared to other cell types. All reconstructed morphologies represent an important resource for computational neuroscientists, as morphological quantitative information can be inferred, to tune simulations that take into account the spatial compartmentalization of the different cell types.

ON selectivity in the Drosophila visual system is a multisynaptic process involving both glutamatergic and GABAergic inhibition

Sensory systems sequentially extract increasingly complex features. ON and OFF pathways, for example, encode increases or decreases of a stimulus from a common input. This ON/OFF pathway split is thought to occur at individual synaptic connections through a sign-inverting synapse in one of the pathways. Here, we show that ON selectivity is a multisynaptic process in the Drosophila visual system. A pharmacogenetics approach demonstrates that both glutamatergic inhibition through GluClα and GABAergic inhibition through Rdl mediate ON responses. Although neurons postsynaptic to the glutamatergic ON pathway input L1 lose all responses in GluClα mutants, they are resistant to a cell-type-specific loss of GluClα. This shows that ON selectivity is distributed across multiple synapses, and raises the possibility that cell-type-specific manipulations might reveal similar strategies in other sensory systems. Thus, sensory coding is more distributed than predicted by simple circuit motifs, allowing for robust neural processing.

Constraining computational models using electron microscopy wiring diagrams

Numerous efforts to generate "connectomes," or synaptic wiring diagrams, of large neural circuits or entire nervous systems are currently underway. These efforts promise an abundance of data to guide theoretical models of neural computation and test their predictions. However, there is not yet a standard set of tools for incorporating the connectivity constraints that these datasets provide into the models typically studied in theoretical neuroscience. This article surveys recent approaches to building models with constrained wiring diagrams and the insights they have provided. It also describes challenges and the need for new techniques to scale these approaches to ever more complex datasets.

Selective suppression and recall of long-term memories in Drosophila

Adaptive decision-making depends on the formation of novel memories. In Drosophila, the mushroom body (MB) is the site of associative olfactory long-term memory (LTM) storage. However, due to the sparse and stochastic representation of olfactory information in Kenyon cells (KCs), genetic access to individual LTMs remains elusive. Here, we develop a cAMP response element (CRE)-activity–dependent memory engram label (CAMEL) tool that genetically tags KCs responding to the conditioned stimulus (CS). CAMEL activity depends on protein-synthesis–dependent aversive LTM conditioning and reflects the time course of CRE binding protein 2 (CREB2) activity during natural memory formation. We demonstrate that inhibition of LTM-induced CAMEL neurons reduces memory expression and that artificial optogenetic reactivation is sufficient to evoke aversive behavior phenocopying memory recall. Together, our data are consistent with CAMEL neurons marking a subset of engram KCs encoding individual memories. This study provides new insights into memory circuitry organization and an entry point towards cellular and molecular understanding of LTM storage.

A novel genetic approach enables the visualization and manipulation of memory engram cells in Drosophila, providing a key methodological opportunity to characterize associative memory at the cellular and circuit level.

A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive.

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Hunger motivates persistent food odor tracking even without reward

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Two synaptically connected MBONs, -γ1pedc>αβ and -α2sc, regulate odor tracking

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Octopamine neurons connect feeding and counteract MBON and odor tracking

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Dopaminergic neurons and Dop1R2 signaling promote persistent tracking

A Student's Guide to Neural Circuit Tracing

The mammalian nervous system is comprised of a seemingly infinitely complex network of specialized synaptic connections that coordinate the flow of information through it. The field of connectomics seeks to map the structure that underlies brain function at resolutions that range from the ultrastructural, which examines the organization of individual synapses that impinge upon a neuron, to the macroscopic, which examines gross connectivity between large brain regions. At the mesoscopic level, distant and local connections between neuronal populations are identified, providing insights into circuit-level architecture. Although neural tract tracing techniques have been available to experimental neuroscientists for many decades, considerable methodological advances have been made in the last 20 years due to synergies between the fields of molecular biology, virology, microscopy, computer science and genetics. As a consequence, investigators now enjoy an unprecedented toolbox of reagents that can be directed against selected subpopulations of neurons to identify their efferent and afferent connectomes. Unfortunately, the intersectional nature of this progress presents newcomers to the field with a daunting array of technologies that have emerged from disciplines they may not be familiar with. This review outlines the current state of mesoscale connectomic approaches, from data collection to analysis, written for the novice to this field. A brief history of neuroanatomy is followed by an assessment of the techniques used by contemporary neuroscientists to resolve mesoscale organization, such as conventional and viral tracers, and methods of selecting for sub-populations of neurons. We consider some weaknesses and bottlenecks of the most widely used approaches for the analysis and dissemination of tracing data and explore the trajectories that rapidly developing neuroanatomy technologies are likely to take.

Visualization of insect metamorphosis

Metamorphosis and, in particular, holometaboly, the development of organisms through a series of discrete stages (egg, larva, pupa, adult) that hardly resemble one another but are finely adapted to specific roles in the life cycle of the organism, has fascinated and mystified humans throughout history. However, it can be difficult to visualize the dramatic changes that occur during holometaboly without destructive sampling, traditionally through histology. However, advances in imaging technologies developed mainly for medical sciences have been applied to studies of insect metamorphosis over the past couple of decades. These include micro-computed tomography, magnetic resonance imaging and optical coherence tomography. A major advantage of these techniques is that they are rapid and non-destructive, enabling virtual dissection of an organism in any plane by anyone who has access to the image files and the necessary software. They can also be applied in some cases to visualize metamorphosis in vivo, including the periods of most rapid and dramatic morphological change. This review focusses on visualizing the intra-puparial holometabolous metamorphosis of cyclorraphous flies (Diptera), including the primary model organism for all genetic investigations, Drosophila melanogaster, and the blow flies of medical, veterinary and forensic importance, but also discusses similar studies on other insect orders. This article is part of the theme issue 'The evolution of complete metamorphosis'.

Revealing the Synaptic Hodology of Mammalian Neural Circuits With Multiscale Neurocartography

The functional features of neural circuits are determined by a combination of properties that range in scale from projections systems across the whole brain to molecular interactions at the synapse. The burgeoning field of neurocartography seeks to map these relevant features of brain structure—spanning a volume ∼20 orders of magnitude—to determine how neural circuits perform computations supporting cognitive function and complex behavior. Recent technological breakthroughs in tissue sample preparation, high-throughput electron microscopy imaging, and automated image analyses have produced the first visualizations of all synaptic connections between neurons of invertebrate model systems. However, the sheer size of the central nervous system in mammals implies that reconstruction of the first full brain maps at synaptic scale may not be feasible for decades. In this review, we outline existing and emerging technologies for neurocartography that complement electron microscopy-based strategies and are beginning to derive some basic organizing principles of circuit hodology at the mesoscale, microscale, and nanoscale. Specifically, we discuss how a host of light microscopy techniques including array tomography have been utilized to determine both long-range and subcellular organizing principles of synaptic connectivity. In addition, we discuss how new techniques, such as two-photon serial tomography of the entire mouse brain, have become attractive approaches to dissect the potential connectivity of defined cell types. Ultimately, principles derived from these techniques promise to facilitate a conceptual understanding of how connectomes, and neurocartography in general, can be effectively utilized toward reaching a mechanistic understanding of circuit function.

The Excitatory, the Inhibitory, and the Modulatory: Mapping Chemical Neurotransmission in the Brain

In this issue of Neuron, Deng et al. (2019) report the generation of a new set of tools to manipulate the entire set of neurotransmitters, neuromodulators, neuropeptides, and their receptors-the "chemoconnectome"-in Drosophila.

Bringing Microscopy-By-Sequencing into View

The spatial distribution of molecules and cells is fundamental to understanding biological systems. Traditionally, microscopies based on electromagnetic waves such as visible light have been used to localize cellular components by direct visualization. However, these techniques suffer from limitations of transmissibility and throughput. Complementary to optical approaches, biochemical techniques such as crosslinking can colocalize molecules without suffering the same limitations. However, biochemical approaches are often unable to combine individual colocalizations into a map across entire cells or tissues. Microscopy-by-sequencing techniques aim to biochemically colocalize DNA-barcoded molecules and, by tracking their thus unique identities, reconcile all colocalizations into a global spatial map. Here, we review this new field and discuss its enormous potential to answer a broad spectrum of questions.

Iron-Sequestering Nanocompartments as Multiplexed Electron Microscopy Gene Reporters

Multicolored gene reporters for light microscopy are indispensable for biomedical research, but equivalent genetic tools for electron microscopy (EM) are still rare despite the increasing importance of nanometer resolution for reverse engineering of molecular machinery and reliable mapping of cellular circuits. We here introduce the fully genetic encapsulin/cargo system of Quasibacillus thermotolerans (Qt), which in combination with the recently characterized encapsulin system from Myxococcus xanthus (Mx) enables multiplexed gene reporter imaging via conventional transmission electron microscopy (TEM) in mammalian cells. Cryo-electron reconstructions revealed that the Qt encapsulin shell self-assembles to nanospheres with T = 4 icosahedral symmetry and a diameter of ∼43 nm harboring two putative pore regions at the 5-fold and 3-fold axes. We also found that upon heterologous expression in mammalian cells, the native cargo is autotargeted to the inner surface of the shell and exhibits ferroxidase activity leading to efficient intraluminal iron biomineralization, which enhances cellular TEM contrast. We furthermore demonstrate that the two differently sized encapsulins of Qt and Mx do not intermix and can be robustly differentiated by conventional TEM via a deep learning classifier to enable automated multiplexed EM gene reporter imaging.

MagC, magnetic collection of ultrathin sections for volumetric correlative light and electron microscopy

The non-destructive collection of ultrathin sections on silicon wafers for post-embedding staining and volumetric correlative light and electron microscopy traditionally requires exquisite manual skills and is tedious and unreliable. In MagC introduced here, sample blocks are augmented with a magnetic resin enabling the remote actuation and collection of hundreds of sections on wafer. MagC allowed the correlative visualization of neuroanatomical tracers within their ultrastructural volumetric electron microscopy context.

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.

Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron

Serotonin plays different roles across networks within the same sensory modality. Previously, we used whole-cell electrophysiology in Drosophila to show that serotonergic neurons innervating the first olfactory relay are inhibited by odorants (Zhang and Gaudry, 2016). Here we show that network-spanning serotonergic neurons segregate information about stimulus features, odor intensity and identity, by using opposing coding schemes in different olfactory neuropil. A pair of serotonergic neurons (the CSDns) innervate the antennal lobe and lateral horn, which are first and second order neuropils. CSDn processes in the antennal lobe are inhibited by odors in an identity independent manner. In the lateral horn, CSDn processes are excited in an odor identity dependent manner. Using functional imaging, modeling, and EM reconstruction, we demonstrate that antennal lobe derived inhibition arises from local GABAergic inputs and acts as a means of gain control on branch-specific inputs that the CSDns receive within the lateral horn.

An atlas of nano-enabled neural interfaces

Advances in microscopy and molecular strategies have allowed researchers to gain insight into the intricate organization of the mammalian brain and the roles that neurons play in processing information. Despite vast progress, therapeutic strategies for neurological disorders remain limited, owing to a lack of biomaterials for sensing and modulating neuronal signalling in vivo. Therefore, there is a pressing need for developing material-based tools that can form seamless biointerfaces and interrogate the brain with unprecedented resolution. In this Review, we discuss important considerations in material design and implementation, highlight recent breakthroughs in neural sensing and modulation, and propose future directions in neurotechnology research. Our goal is to create an atlas for nano-enabled neural interfaces and to demonstrate how emerging nanotechnologies can interrogate neural systems spanning multiple biological length scales.

Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity

The dimensionality of a network's collective activity is of increasing interest in neuroscience. This is because dimensionality provides a compact measure of how coordinated network-wide activity is, in terms of the number of modes (or degrees of freedom) that it can independently explore. A low number of modes suggests a compressed low dimensional neural code and reveals interpretable dynamics [1], while findings of high dimension may suggest flexible computations [2, 3]. Here, we address the fundamental question of how dimensionality is related to connectivity, in both autonomous and stimulus-driven networks. Working with a simple spiking network model, we derive three main findings. First, the dimensionality of global activity patterns can be strongly, and systematically, regulated by local connectivity structures. Second, the dimensionality is a better indicator than average correlations in determining how constrained neural activity is. Third, stimulus evoked neural activity interacts systematically with neural connectivity patterns, leading to network responses of either greater or lesser dimensionality than the stimulus.

Inhibitory muscarinic acetylcholine receptors enhance aversive olfactory learning in adult Drosophila

Olfactory associative learning in Drosophila is mediated by synaptic plasticity between the Kenyon cells of the mushroom body and their output neurons. Both Kenyon cells and their inputs from projection neurons are cholinergic, yet little is known about the physiological function of muscarinic acetylcholine receptors in learning in adult flies. Here, we show that aversive olfactory learning in adult flies requires type A muscarinic acetylcholine receptors (mAChR-A), particularly in the gamma subtype of Kenyon cells. mAChR-A inhibits odor responses and is localized in Kenyon cell dendrites. Moreover, mAChR-A knockdown impairs the learning-associated depression of odor responses in a mushroom body output neuron. Our results suggest that mAChR-A function in Kenyon cell dendrites is required for synaptic plasticity between Kenyon cells and their output neurons.

DNA sequencing in high-throughput neuroanatomy

Mapping brain connectivity at single cell resolution is critical for understanding brain structure. For decades, such mapping has been principally approached with microscopy techniques, aiming to visualize neurons and their connections. However, these techniques are often very labor intensive and do not scale well to the complexity of mammalian brains. We recently leveraged the speed and parallelization of DNA sequencing to map the projections of thousands of single neurons in single experiments, and to map cortical mesoscale connectivity in single mice. Here, I review the state of sequencing-based neuroanatomy, and discuss future directions in synaptic connectivity mapping and comparative connectomics.

Recent Advances in the Genetic Dissection of Neural Circuits in Drosophila

Nervous systems endow animals with cognition and behavior. To understand how nervous systems control behavior, neural circuits mediating distinct functions need to be identified and characterized. With superior genetic manipulability, Drosophila is a model organism at the leading edge of neural circuit analysis. We briefly introduce the state-of-the-art genetic tools that permit precise labeling of neurons and their interconnectivity and investigating what is happening in the brain of a behaving animal and manipulating neurons to determine how behaviors are affected. Brain-wide wiring diagrams, created by light and electron microscopy, bring neural circuit analysis to a new level and scale. Studies enabled by these tools advances our understanding of the nervous system in relation to cognition and behavior.

Flies spring a surprise

A combination of genetic, anatomical and physiological techniques has revealed that the lateral horn, a region of the brain involved in olfaction in flies, has many more types of neurons than expected.

Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

Functional and anatomical specificity in a higher olfactory centre

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.

Role of neurons in the control of immune defense

Studies in recent years have strengthened the notion that neural mechanisms are involved in the control of immune responses. From initial studies that highlighted the vagus nerve control of inflammatory responses in vertebrates, many advances have been made, including the dissection of specific neural circuits that are involved in controlling immunity. Part of this has been facilitated by the use of a tractable model animal, Caenorhabditis elegans, in which individual neurons involved in sensing pathogens and controlling the immune response have been identified. Importantly, some of the underlying mechanisms involved in the neural control of immune pathways appear to be present in evolutionarily diverse species. This review focuses on some major developments in vertebrates and C. elegans, and how these discoveries may lead to advances in understanding neural-immune connections that govern inflammatory responses.

Convolutional nets for reconstructing neural circuits from brain images acquired by serial section electron microscopy

Neural circuits can be reconstructed from brain images acquired by serial section electron microscopy. Image analysis has been performed by manual labor for half a century, and efforts at automation date back almost as far. Convolutional nets were first applied to neuronal boundary detection a dozen years ago, and have now achieved impressive accuracy on clean images. Robust handling of image defects is a major outstanding challenge. Convolutional nets are also being employed for other tasks in neural circuit reconstruction: finding synapses and identifying synaptic partners, extending or pruning neuronal reconstructions, and aligning serial section images to create a 3D image stack. Computational systems are being engineered to handle petavoxel images of cubic millimeter brain volumes.

Big data in nanoscale connectomics, and the greed for training labels

The neurosciences have developed methods that outpace most other biomedical fields in terms of acquired bytes. We review how the information content and analysis challenge of such data indicates that electron microscopy (EM)-based connectomics is an especially hard problem. Here, as in many other current machine learning applications, the need for excessive amounts of labelled data while utilizing only a small fraction of available raw image data for algorithm training illustrates the still fundamental gap between artificial and biological intelligence. Substantial improvements of label and energy efficiency in machine learning may be required to address the formidable challenge of acquiring the nanoscale connectome of a human brain.

Novel Technological Advances in Functional Connectomics in C. elegans

The complete structure and connectivity of the Caenorhabditis elegans nervous system ("mind of a worm") was first published in 1986, representing a critical milestone in the field of connectomics. The reconstruction of the nervous system (connectome) at the level of synapses provided a unique perspective of understanding how behavior can be coded within the nervous system. The following decades have seen the development of technologies that help understand how neural activity patterns are connected to behavior and modulated by sensory input. Investigations on the developmental origins of the connectome highlight the importance of role of neuronal cell lineages in the final connectivity matrix of the nervous system. Computational modeling of neuronal dynamics not only helps reconstruct the biophysical properties of individual neurons but also allows for subsequent reconstruction of whole-organism neuronal network models. Hence, combining experimental datasets with theoretical modeling of neurons generates a better understanding of organismal behavior. This review discusses some recent technological advances used to analyze and perturb whole-organism neuronal function along with developments in computational modeling, which allows for interrogation of both local and global neural circuits, leading to different behaviors. Combining these approaches will shed light into how neural networks process sensory information to generate the appropriate behavioral output, providing a complete understanding of the worm nervous system.

Optical properties of adult Drosophila brains in one-, two-, and three-photon microscopy

Drosophila is widely used in connectome studies due to its small brain size, sophisticated genetic tools, and the most complete single-neuron-based anatomical brain map. Surprisingly, even the brain thickness is only 200-μm, common Ti:sapphire-based two-photon excitation cannot penetrate, possibly due to light aberration/scattering of trachea. Here we quantitatively characterized scattering and light distortion of trachea-filled tissues, and found that trachea-induced light distortion dominates at long wavelength by comparing one-photon (488-nm), two-photon (920-nm), and three-photon (1300-nm) excitations. Whole-Drosophila-brain imaging is achieved by reducing tracheal light aberration/scattering via brain-degassing or long-wavelength excitation at 1300-nm. Our work paves the way toward constructing whole-brain connectome in a living Drosophila.

Semi-automated 3D segmentation of human skeletal muscle using Focused Ion Beam-Scanning Electron Microscopic images

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) is an imaging approach that enables analysis of the 3D architecture of cells and tissues at resolutions that are 1-2 orders of magnitude higher than that possible with light microscopy. The slow speeds of data collection and manual segmentation are two critical problems that limit the more extensive use of FIB-SEM technology. Here, we present an easily accessible robust method that enables rapid, large-scale acquisition of data from tissue specimens, combined with an approach for semi-automated data segmentation using the open-source machine learning Weka segmentation software, which dramatically increases the speed of image analysis. We demonstrate the feasibility of these methods through the 3D analysis of human muscle tissue by showing that our process results in an improvement in speed of up to three orders of magnitude as compared to manual approaches for data segmentation. All programs and scripts we use are open source and are immediately available for use by others.

Multiplexed peroxidase-based electron microscopy labeling enables simultaneous visualization of multiple cell types

Electron microscopy (EM) is a powerful tool for circuit mapping, but identifying specific cell types in EM datasets remains a major challenge. Here we describe a technique enabling simultaneous visualization of multiple, genetically identified neuronal populations so that synaptic interactions between them can be unequivocally defined. We present 15 AAV constructs and six mouse reporter lines for multiplexed EM labeling in the mammalian nervous system. These reporters feature dAPEX2, which exhibits dramatically improved signal compared to previously described ascorbate peroxidases. By targeting this enhanced peroxidase to different subcellular compartments, multiple orthogonal reporters can be simultaneously visualized and distinguished under EM using a protocol compatible with existing EM pipelines. Proof-of-principle double and triple EM labeling experiments demonstrated synaptic connections between primary afferents, descending cortical inputs, and inhibitory interneurons in the spinal cord dorsal horn. Our multiplexed peroxidase-based EM labeling system should therefore greatly facilitate analysis of connectivity in the nervous system.

The development and assembly of the Drosophila adult ventral nerve cord

In order to generate complex motor outputs, the nervous system integrates multiple sources of sensory information that ultimately controls motor neurons to generate coordinated movements. The neural circuits that integrate higher order commands from the brain and generate motor outputs are located in the nerve cord of the central nervous system. Recently, genetic access to distinct functional subtypes that make up the Drosophila adult ventral nerve cord has significantly begun to advance our understanding of the structural organization and functions of the neural circuits coordinating motor outputs. Moreover, lineage-tracing and genetic intersection tools have been instrumental in deciphering the developmental mechanisms that generate and assemble the functional units of the adult nerve cord. Together, the Drosophila adult ventral nerve cord is emerging as a powerful system to understand the development and function of neural circuits that are responsible for coordinating complex motor outputs.

Chemoconnectomics: Mapping Chemical Transmission in Drosophila

We define the chemoconnectome (CCT) as the entire set of neurotransmitters, neuromodulators, neuropeptides, and their receptors underlying chemotransmission in an animal. We have generated knockout lines of Drosophila CCT genes for functional investigations and knockin lines containing Gal4 and other tools for examining gene expression and manipulating neuronal activities, with a versatile platform allowing genetic intersections and logic gates. CCT reveals the coexistence of specific transmitters but mutual exclusion of the major inhibitory and excitatory transmitters in the same neurons. One neuropeptide and five receptors were detected in glia, with octopamine β2 receptor functioning in glia. A pilot screen implicated 41 genes in sleep regulation, with the dopamine receptor Dop2R functioning in neurons expressing the peptides Dilp2 and SIFa. Thus, CCT is a novel concept, chemoconnectomics a new approach, and CCT tool lines a powerful resource for systematic investigations of chemical-transmission-mediated neural signaling circuits underlying behavior and cognition.

Acoustic Pattern Recognition and Courtship Songs: Insights from Insects

Across the animal kingdom, social interactions rely on sound production and perception. From simple cricket chirps to more elaborate bird songs, animals go to great lengths to communicate information critical for reproduction and survival via acoustic signals. Insects produce a wide array of songs to attract a mate, and the intended receivers must differentiate these calls from competing sounds, analyze the quality of the sender from spectrotemporal signal properties, and then determine how to react. Insects use numerically simple nervous systems to analyze and respond to courtship songs, making them ideal model systems for uncovering the neural mechanisms underlying acoustic pattern recognition. We highlight here how the combination of behavioral studies and neural recordings in three groups of insects-crickets, grasshoppers, and fruit flies-reveals common strategies for extracting ethologically relevant information from acoustic patterns and how these findings might translate to other systems.