Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy.
TL;DR: This work developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development and performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo.
Abstract: Simultaneous multiview light-sheet microscopy using two illumination and two detection arms with one- or two-photon illumination is coupled to a fast data acquisition framework and analysis pipeline for quantitative imaging and tracking of individual cells and the developing nervous system throughout a living fly embryo. A related paper by Krzic et al. is also in this issue.
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01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
Howard Hughes Medical Institute1, Florida State University2, University of the Sciences3, National Institutes of Health4, University of Minnesota5, University of Cambridge6, University of California, San Francisco7, University of Tennessee8, Max Planck Society9, Johns Hopkins University10, Duke University11
TL;DR: A new microscope using ultrathin light sheets derived from two-dimensional optical lattices is developed, demonstrating the performance advantages of lattice light-sheet microscopy compared with previous techniques and highlighted phenomena that, when seen at increased spatiotemporal detail, may hint at previously unknown biological mechanisms.
Abstract: Although fluorescence microscopy provides a crucial window into the physiology of living specimens, many biological processes are too fragile, are too small, or occur too rapidly to see clearly with existing tools. We crafted ultrathin light sheets from two-dimensional optical lattices that allowed us to image three-dimensional (3D) dynamics for hundreds of volumes, often at subsecond intervals, at the diffraction limit and beyond. We applied this to systems spanning four orders of magnitude in space and time, including the diffusion of single transcription factor molecules in stem cell spheroids, the dynamic instability of mitotic microtubules, the immunological synapse, neutrophil motility in a 3D matrix, and embryogenesis in Caenorhabditis elegans and Drosophila melanogaster. The results provide a visceral reminder of the beauty and the complexity of living systems.
1,585 citations
Cites background from "Quantitative high-speed imaging of ..."
...This approach has proven powerful for noninvasive four-dimensional (4D) imaging of embryos at single-cell resolution (5, 6); however, conventional light sheets created with Gaussian beams (Fig....
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07 Nov 2014
TL;DR: A guide to using some of the recently added advanced μManager features, including hardware synchronization, simultaneous use of multiple cameras, projection of patterned light onto a specimen, live slide mapping, imaging with multi-well plates, particle localization and tracking, and high-speed imaging.
Abstract: μManager is an open-source, cross-platform desktop application, to control a wide variety of motorized microscopes, scientific cameras, stages, illuminators, and other microscope accessories. Since its inception in 2005, μManager has grown to support a wide range of microscopy hardware and is now used by thousands of researchers around the world. The application provides a mature graphical user interface and offers open programming interfaces to facilitate plugins and scripts. Here, we present a guide to using some of the recently added advanced μManager features, including hardware synchronization, simultaneous use of multiple cameras, projection of patterned light onto a specimen, live slide mapping, imaging with multi-well plates, particle localization and tracking, and high-speed imaging.
1,547 citations
Cites background from "Quantitative high-speed imaging of ..."
...High speed sCMOS cameras have proven useful for imaging three-dimensional evolving specimens [5] and advanced applications such as super-resolution microscopy [6]....
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TL;DR: Light-sheet microscopy is used to record activity 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.
Abstract: 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.
1,231 citations
TL;DR: The interplay between tissue mechanics and biochemical signaling orchestrates tissue morphogenesis and patterning in development.
951 citations
Cites background from "Quantitative high-speed imaging of ..."
...…and temporal resolution and in the development of image analysis tools to quantify cell/tissue dynamics (Montero et al., 2005; Kwon et al., 2008; Keller et al., 2008; Blanchard et al., 2009; Olivier et al., 2010; Bosveld et al., 2012; Tomer et al., 2012; Gao et al., 2012; Krzic et al., 2012)....
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...In recent years, considerable progress has been made in the development of image acquisition tools to record dynamic changes in cell and tissue shapes at high spatial and temporal resolution and in the development of image analysis tools to quantify cell/tissue dynamics (Montero et al., 2005; Kwon et al., 2008; Keller et al., 2008; Blanchard et al., 2009; Olivier et al., 2010; Bosveld et al., 2012; Tomer et al., 2012; Gao et al., 2012; Krzic et al., 2012)....
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References
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17 Aug 2006TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
22,840 citations
01 Jan 2004
TL;DR: ImageJ is an open source Java-written program that is used for many imaging applications, including those that that span the gamut from skin analysis to neuroscience, and can read most of the widely used and significant formats used in biomedical images.
Abstract: Wayne Rasband of NIH has created ImageJ, an open source Java-written program that is now at version 1.31 and is used for many imaging applications, including those that that span the gamut from skin analysis to neuroscience. ImageJ is in the public domain and runs on any operating system (OS). ImageJ is easy to use and can do many imaging manipulations. A very large and knowledgeable group makes up the user community for ImageJ. Topics covered are imaging abilities; cross platform; image formats support as of June 2004; extensions, including macros and plug-ins; and imaging library. NIH reports tens of thousands of downloads at a rate of about 24,000 per month currently. ImageJ can read most of the widely used and significant formats used in biomedical images. Manipulations supported are read/write of image files and operations on separate pixels, image regions, entire images, and volumes (stacks in ImageJ). Basic operations supported include convolution, edge detection, Fourier transform, histogram and particle analyses, editing and color manipulation, and more advanced operations, as well as visualization. For assistance in using ImageJ, users e-mail each other, and the user base is highly knowledgeable and will answer requests on the mailing list. A thorough manual with many examples and illustrations has been written by Tony Collins of the Wright Cell Imaging Facility at Toronto Western Research Institute and is available, along with other listed resources, via the Web.
12,060 citations
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations