Automated reconstruction of neural connectivity graphs from electron microscopy image stacks is an essential step towards large-scale neural circuit mapping. While significant progress has recently been made in automated segmentation of neurons and detection of synapses, the problem of synaptic partner assignment for polyadic (one-to-many) synapses, prevalent in the Drosophila brain, remains unsolved. In this contribution, we propose a method which automatically assigns pre- and postsynaptic roles to neurites adjacent to a synaptic site. The method constructs a probabilistic graphical model over potential synaptic partner pairs which includes factors to account for a high rate of one-to-many connections, as well as the possibility of the same neuron to be pre-synaptic in one synapse and post-synaptic in another. The algorithm has been validated on a publicly available stack of ssTEM images of Drosophila neural tissue and has been shown to reconstruct most of the synaptic relations correctly.

Imaging fast cellular dynamics across large specimens requires high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To meet these requirements, we developed isotropic multiview (IsoView) light-sheet microscopy, which rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. Combining these four views by means of high-throughput multiview deconvolution yields images with high resolution in all three dimensions. We demonstrate whole-animal functional imaging of Drosophila larvae at a spatial resolution of 1.1-2.5 μm and temporal resolution of 2 Hz for several hours. We also present spatially isotropic whole-brain functional imaging in Danio rerio larvae and spatially isotropic multicolor imaging of fast cellular dynamics across gastrulating Drosophila embryos. Compared with conventional light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

The body of an animal influences how the nervous system produces behavior. Therefore, detailed modeling of the neural control of sensorimotor behavior requires a detailed model of the body. Here we contribute an anatomically-detailed biomechanical whole-body model of the fruit fly Drosophila melanogaster in the MuJoCo physics engine. Our model is general-purpose, enabling the simulation of diverse fly behaviors, both on land and in the air. We demonstrate the generality of our model by simulating realistic locomotion, both flight and walking. To support these behaviors, we have extended MuJoCo with phenomenological models of fluid forces and adhesion forces. Through data-driven end-to-end reinforcement learning, we demonstrate that these advances enable the training of neural network controllers capable of realistic locomotion along complex trajectories based on high-level steering control signals. We demonstrate the use of visual sensors and the re-use of a pre-trained general-purpose flight controller by training the model to perform visually guided flight tasks. Our project is an open-source platform for modeling neural control of sensorimotor behavior in an embodied context.Competing Interest StatementThe authors have declared no competing interest.

The body of an animal influences how its nervous system generates behavior1. Accurately modeling the neural control of sensorimotor behavior requires an anatomically detailed biomechanical representation of the body. Here, we introduce a whole-body model of the fruit fly Drosophila melanogaster in a physics simulator. Designed as a general-purpose framework, our model enables the simulation of diverse fly behaviors, including both terrestrial and aerial locomotion. We validate its versatility by replicating realistic walking and flight behaviors. To support these behaviors, we develop new phenomenological models for fluid and adhesion forces. Using data-driven, end-to-end reinforcement learning we train neural network controllers capable of generating naturalistic locomotion along complex trajectories in response to high-level steering commands. Additionally, we show the use of visual sensors and hierarchical motor control, training a high-level controller to reuse a pre-trained low-level flight controller to perform visually guided flight tasks. Our model serves as an open-source platform for studying the neural control of sensorimotor behavior in an embodied context.

Preprint: www.biorxiv.org/content/early/2024/03/14/2024.03.11.584515

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.

Brain function relies on communication between large populations of neurons across multiple brain areas, a full understanding of which would require knowledge of the time-varying activity of all neurons in the central nervous system. Here we use light-sheet microscopy to record activity, reported through the genetically encoded calcium indicator GCaMP5G, from the entire volume of the brain of the larval zebrafish in vivo at 0.8 Hz, capturing more than 80% of all neurons at single-cell resolution. Demonstrating how this technique can be used to reveal functionally defined circuits across the brain, we identify two populations of neurons with correlated activity patterns. One circuit consists of hindbrain neurons functionally coupled to spinal cord neuropil. The other consists of an anatomically symmetric population in the anterior hindbrain, with activity in the left and right halves oscillating in antiphase, on a timescale of 20 s, and coupled to equally slow oscillations in the inferior olive.

Tissue clearing and light-sheet microscopy have a 100-year-plus history, yet these fields have been combined only recently to facilitate novel experiments and measurements in neuroscience. Since tissue-clearing methods were first combined with modernized light-sheet microscopy a decade ago, the performance of both technologies has rapidly improved, broadening their applications. Here, we review the state of the art of tissue-clearing methods and light-sheet microscopy and discuss applications of these techniques in profiling cells and circuits in mice. We examine outstanding challenges and future opportunities for expanding these techniques to achieve brain-wide profiling of cells and circuits in primates and humans. Such integration will help provide a systems-level understanding of the physiology and pathology of our central nervous system.

Tissue clearing and light-sheet microscopy have a 100-year-plus history, yet these fields have been combined only recently to facilitate novel experiments and measurements in neuroscience. Since tissue-clearing methods were first combined with modernized light-sheet microscopy a decade ago, the performance of both technologies has rapidly improved, broadening their applications. Here, we review the state of the art of tissue-clearing methods and light-sheet microscopy and discuss applications of these techniques in profiling cells and circuits in mice. We examine outstanding challenges and future opportunities for expanding these techniques to achieve brain-wide profiling of cells and circuits in primates and humans. Such integration will help provide a systems-level understanding of the physiology and pathology of our central nervous system.

High-resolution serial-section electron microscopy (ssEM) makes it possible to investigate the dense meshwork of axons, dendrites, and synapses that form neuronal circuits. However, the imaging scale required to comprehensively reconstruct these structures is more than ten orders of magnitude smaller than the spatial extents occupied by networks of interconnected neurons, some of which span nearly the entire brain. Difficulties in generating and handling data for large volumes at nanoscale resolution have thus restricted vertebrate studies to fragments of circuits. These efforts were recently transformed by advances in computing, sample handling, and imaging techniques, but high-resolution examination of entire brains remains a challenge. Here, we present ssEM data for the complete brain of a larval zebrafish (Danio rerio) at 5.5 days post-fertilization. Our approach utilizes multiple rounds of targeted imaging at different scales to reduce acquisition time and data management requirements. The resulting dataset can be analysed to reconstruct neuronal processes, permitting us to survey all myelinated axons (the projectome). These reconstructions enable precise investigations of neuronal morphology, which reveal remarkable bilateral symmetry in myelinated reticulospinal and lateral line afferent axons. We further set the stage for whole-brain structure-function comparisons by co-registering functional reference atlases and in vivo two-photon fluorescence microscopy data from the same specimen. All obtained images and reconstructions are provided as an open-access resource.