In the mouse, each class of olfactory receptor neurons expressing a given odorant receptor converges their axons onto two specific glomeruli in the olfactory bulb (OB), thereby creating an odor map. How is this map represented in the olfactory cortex? Here we combine rabies virusdependent retrograde mono-transsynaptic labeling with genetics to control the location, number and type of 'starter' cortical neurons, from which we trace their presynaptic neurons. We find that individual cortical neurons receive input from multiple mitral cells representing broadly distributed glomeruli. Different cortical areas represent the OB input differently. For example, the cortical amygdala preferentially receives dorsal OB input, whereas the piriform cortex samples the whole OB without obvious bias. These differences likely reflect different functions of these cortical areas in mediating innate odor preference or associative memory. The transsynaptic labeling method described here should be widely applicable to mapping connections throughout the mouse nervous system. The functions of mammalian brains are based on activity patterns of large numbers of interconnected neurons that form information processing circuits. Neural circuits consist of local connections, where pre-and post-synaptic partners reside within the same brain area, and long-distance connections, which link different areas. Local connections can be predicted by axon and dendrite reconstructions1, and confirmed by physiological recording and stimulation methods2. Long-distance connections are more difficult to map, as commonly used methods can only trace bulk projections with a coarse resolution. Most methods cannot distinguish axons in passing from those that form synapses, or pinpoint neuronal types to

Live imaging of large biological specimens is fundamentally limited by the short optical penetration depth of light microscopes. To maximize physical coverage, we developed the SiMView technology framework for high-speed in vivo imaging, which records multiple views of the specimen simultaneously. SiMView consists of a light-sheet microscope with four synchronized optical arms, real-time electronics for long-term sCMOS-based image acquisition at 175 million voxels per second, and computational modules for high-throughput image registration, segmentation, tracking and real-time management of the terabytes of multiview data recorded per specimen. We developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development. We furthermore performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo. SiMView data sets provide quantitative morphological information even for fast global processes and enable accurate automated cell tracking in the entire early embryo.

Highlights d Adaptive light-sheet microscopy captures mouse development at the single-cell level d We analyzed embryo-wide cell dynamics from gastrulation to early organogenesis d We reconstructed high-resolution fate maps and maps of tissue morphogenesis d We created a statistical, dynamic atlas of development from multiple embryos

The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (i) generality by reconstructing cell lineages in four-dimensional, terabyte-sized image data sets of fruit fly, zebrafish and mouse embryos acquired with three types of fluorescence microscopes, (ii) scalability by analyzing advanced stages of development with up to 20,000 cells per time point at 26,000 cells min(-1) on a single computer workstation and (iii) ease of use by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities. Using our system, we performed the first cell lineage reconstruction of early Drosophila melanogaster nervous system development, revealing neuroblast dynamics throughout an entire embryo.

Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware.

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.

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.

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