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      Quantitative neuroanatomy of all Purkinje cells with light sheet microscopy and high-throughput image analysis

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          Abstract

          Characterizing the cytoarchitecture of mammalian central nervous system on a brain-wide scale is becoming a compelling need in neuroscience. For example, realistic modeling of brain activity requires the definition of quantitative features of large neuronal populations in the whole brain. Quantitative anatomical maps will also be crucial to classify the cytoarchtitectonic abnormalities associated with neuronal pathologies in a high reproducible and reliable manner. In this paper, we apply recent advances in optical microscopy and image analysis to characterize the spatial distribution of Purkinje cells (PCs) across the whole cerebellum. Light sheet microscopy was used to image with micron-scale resolution a fixed and cleared cerebellum of an L7-GFP transgenic mouse, in which all PCs are fluorescently labeled. A fast and scalable algorithm for fully automated cell identification was applied on the image to extract the position of all the fluorescent PCs. This vectorized representation of the cell population allows a thorough characterization of the complex three-dimensional distribution of the neurons, highlighting the presence of gaps inside the lamellar organization of PCs, whose density is believed to play a significant role in autism spectrum disorders. Furthermore, clustering analysis of the localized somata permits dividing the whole cerebellum in groups of PCs with high spatial correlation, suggesting new possibilities of anatomical partition. The quantitative approach presented here can be extended to study the distribution of different types of cell in many brain regions and across the whole encephalon, providing a robust base for building realistic computational models of the brain, and for unbiased morphological tissue screening in presence of pathologies and/or drug treatments.

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          Most cited references31

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          Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy.

          A long-standing goal of biology is to map the behavior of all cells during vertebrate embryogenesis. We developed digital scanned laser light sheet fluorescence microscopy and recorded nuclei localization and movement in entire wild-type and mutant zebrafish embryos over the first 24 hours of development. Multiview in vivo imaging at 1.5 billion voxels per minute provides "digital embryos," that is, comprehensive databases of cell positions, divisions, and migratory tracks. Our analysis of global cell division patterns reveals a maternally defined initial morphodynamic symmetry break, which identifies the embryonic body axis. We further derive a model of germ layer formation and show that the mesendoderm forms from one-third of the embryo's cells in a single event. Our digital embryos, with 55 million nucleus entries, are provided as a resource.
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            The log-dynamic brain: how skewed distributions affect network operations.

            We often assume that the variables of functional and structural brain parameters - such as synaptic weights, the firing rates of individual neurons, the synchronous discharge of neural populations, the number of synaptic contacts between neurons and the size of dendritic boutons - have a bell-shaped distribution. However, at many physiological and anatomical levels in the brain, the distribution of numerous parameters is in fact strongly skewed with a heavy tail, suggesting that skewed (typically lognormal) distributions are fundamental to structural and functional brain organization. This insight not only has implications for how we should collect and analyse data, it may also help us to understand how the different levels of skewed distributions - from synapses to cognition - are related to each other.
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              V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets

              The V3D system provides three-dimensional (3D) visualization of gigabyte-sized microscopy image stacks in real time on current laptops and desktops. Combined with highly ergonomic features for selecting an X, Y, Z location of an image directly in 3D space and for visualizing overlays of a variety of surface objects, V3D streamlines the on-line analysis, measurement, and proofreading of complicated image patterns. V3D is cross-platform and can be enhanced by plug-ins. We built V3D-Neuron on top of V3D to reconstruct complex 3D neuronal structures from large brain images. V3D-Neuron enables us to precisely digitize the morphology of a single neuron in a fruit fly brain in minutes, with about 17-fold improvement in reliability and 10-fold savings in time compared to other neuron reconstruction tools. Using V3D-Neuron, we demonstrated the feasibility of building a 3D digital atlas of neurite tracts in the fruit fly brain.
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                Author and article information

                Contributors
                Journal
                Front Neuroanat
                Front Neuroanat
                Front. Neuroanat.
                Frontiers in Neuroanatomy
                Frontiers Media S.A.
                1662-5129
                27 May 2015
                2015
                : 9
                : 68
                Affiliations
                [1] 1National Institute of Optics, National Research Council Sesto Fiorentino, Italy
                [2] 2European Laboratory for Non-Linear Spectroscopy Sesto Fiorentino, Italy
                [3] 3Department of Information Engineering, University of Florence Florence, Italy
                [4] 4Department of Engineering, University Campus Bio-Medico of Rome Rome, Italy
                [5] 5Institute of Histology and Embryology, Catholic University of the Sacred Heart “A. Gemelli”, Rome Italy
                [6] 6Department of Physics and Astronomy, University of Florence Sesto Fiorentino, Italy
                [7] 7International Center for Computational Neurophotonics Sesto Fiorentino, Italy
                Author notes

                Edited by: Kathleen S. Rockland, Boston University School of Medicine, USA

                Reviewed by: José A. Armengol, Universidad Pablo de Olavide, Spain; Yugo Fukazawa, University of Fukui, Japan

                *Correspondence: Ludovico Silvestri, European Laboratory for Non-Linear Spectroscopy, National Institute of Optics, National Research Council, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy silvestri@ 123456lens.unifi.it

                These authors have contributed equally to this work.

                Article
                10.3389/fnana.2015.00068
                4445386
                26074783
                c0c2f3f9-b789-4848-b838-7f1c408a2a34
                Copyright © 2015 Silvestri, Paciscopi, Soda, Biamonte, Iannello, Frasconi and Pavone.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 March 2015
                : 11 May 2015
                Page count
                Figures: 8, Tables: 0, Equations: 1, References: 47, Pages: 11, Words: 0
                Categories
                Neuroanatomy
                Original Research

                Neurosciences
                quantitative neuroanatomy,purkinje cells,cerebellum,light sheet microscopy,image analysis,brain imaging

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