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      Comprehensive cellular‐resolution atlas of the adult human brain

      research-article
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      The Journal of Comparative Neurology
      John Wiley and Sons Inc.
      brain atlas, cerebral cortex, hippocampal formation, thalamus, hypothalamus, amygdala, cerebellum, brainstem, MRI, DWI, cytoarchitecture, parvalbumin, neurofilament protein, RRIDs: AB_10000343, AB_2314904, SCR_014329

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          ABSTRACT

          Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

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          Most cited references67

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          Automatically Parcellating the Human Cerebral Cortex

          B Fischl (2004)
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            Construction of a 3D probabilistic atlas of human cortical structures.

            We describe the construction of a digital brain atlas composed of data from manually delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal volunteers. This labeling was performed according to a set of protocols developed for this project. Pairs of raters were assigned to each structure and trained on the protocol for that structure. Each rater pair was tested for concordance on 6 of the 40 brains; once they had achieved reliability standards, they divided the task of delineating the remaining 34 brains. The data were then spatially normalized to well-known templates using 3 popular algorithms: AIR5.2.5's nonlinear warp (Woods et al., 1998) paired with the ICBM452 Warp 5 atlas (Rex et al., 2003), FSL's FLIRT (Smith et al., 2004) was paired with its own template, a skull-stripped version of the ICBM152 T1 average; and SPM5's unified segmentation method (Ashburner and Friston, 2005) was paired with its canonical brain, the whole head ICBM152 T1 average. We thus produced 3 variants of our atlas, where each was constructed from 40 representative samples of a data processing stream that one might use for analysis. For each normalization algorithm, the individual structure delineations were then resampled according to the computed transformations. We next computed averages at each voxel location to estimate the probability of that voxel belonging to each of the 56 structures. Each version of the atlas contains, for every voxel, probability densities for each region, thus providing a resource for automated probabilistic labeling of external data types registered into standard spaces; we also computed average intensity images and tissue density maps based on the three methods and target spaces. These atlases will serve as a resource for diverse applications including meta-analysis of functional and structural imaging data and other bioinformatics applications where display of arbitrary labels in probabilistically defined anatomic space will facilitate both knowledge-based development and visualization of findings from multiple disciplines.
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              High-resolution intersubject averaging and a coordinate system for the cortical surface.

              The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3-D stereotaxic coordinates rather than on position relative to the 2-D cortical sheet. In order to address the need for a more natural surface-based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface-based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain.
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                Author and article information

                Contributors
                songd@alleninstitute.org
                EdL@alleninstitute.org
                Journal
                J Comp Neurol
                J. Comp. Neurol
                10.1002/(ISSN)1096-9861
                CNE
                The Journal of Comparative Neurology
                John Wiley and Sons Inc. (Hoboken )
                0021-9967
                1096-9861
                15 September 2016
                01 November 2016
                : 524
                : 16 , The Allen Human Brain Reference Atlas ( doiID: 10.1002/cne.v524.16 )
                : 3127-3481
                Affiliations
                [ 1 ]Allen Institute for Brain Science Seattle Washington 98109
                [ 2 ] Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts 02129
                [ 3 ] Zilkha Neurogenetic Institute, and Department of PsychiatryUniversity of Southern California Los Angeles California 90033
                [ 4 ] Department of Neurobiology and Kavli Institute for NeuroscienceYale University School of Medicine New Haven Connecticut 06510
                [ 5 ] Department of PediatricsUniversity of Maryland School of Medicine Baltimore Maryland 21201
                [ 6 ] Fishberg Department of Neuroscience and Friedman Brain InstituteIcahn School of Medicine at Mount Sinai New York New York 11029
                Author notes
                [*] [* ]CORRESPONDENCE TO: Ed S. Lein or Song‐Lin Ding, Allen Institute for Brain Science, Seattle, WA 98109. E‐mail: EdL@ 123456alleninstitute.org , or songd@ 123456alleninstitute.org
                Article
                CNE24080
                10.1002/cne.24080
                5054943
                27418273
                7f3b5de7-a58d-4c34-98b7-d7e4874a52e5
                Copyright © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 20 May 2016
                : 11 July 2016
                : 13 July 2016
                Page count
                Figures: 305, Tables: 3, Pages: 356, Words: 14341
                Funding
                Funded by: National Institute for Neurological Disorders and Stroke
                Award ID: R01NS0525851, R21NS072652, R01NS070963, R01NS08353
                Funded by: Shared Instrumentation Grants
                Award ID: 1S10RR023401, 1S10RR019307 & 1S10RR023043
                Funded by: National Institutes of Health
                Award ID: RC2 MH089921
                Funded by: NIH Blueprint for Neuroscience Research
                Award ID: 5U01‐MH093765
                Funded by: National Institute on Aging
                Award ID: 5R01AG008122 & R01AG016495
                Funded by: National Institute for Biomedical Imaging and Bioengineering
                Award ID: P41EB015896, R01EB006758, R21EB018907 & R01EB01995
                Funded by: Allen Institute for Brain Science
                Categories
                Research Article
                Research Article
                Custom metadata
                2.0
                cne24080
                November 1, 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:07.10.2016

                Neurology
                brain atlas,cerebral cortex,hippocampal formation,thalamus,hypothalamus,amygdala,cerebellum,brainstem,mri,dwi,cytoarchitecture,parvalbumin,neurofilament protein,rrids: ab_10000343,ab_2314904,scr_014329

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