The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

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Abstract

The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T ₁-weighted magnetic resonance (MR) images of 19 rhesus macaque ( Macaca mulatta) animals. Combined with the comprehensive cortical and sub-cortical label map of the NeuroMaps atlas, the INIA19 is equally suitable for studies requiring both spatial normalization and atlas label propagation. Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for skull stripping of new images. This article describes the construction of the template using freely available software tools, as well as the template itself, which is being made available to the scientific community ( http://nitrc.org/projects/inia19/).

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Most cited references 28

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Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter.

Katrin Amunts, Xin Li, Jiangyang Zhang … (2008)

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.

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The SRI24 multichannel atlas of normal adult human brain structure.

Edith Sullivan, Adolf Pfefferbaum, Torsten Rohlfing … (2010)

This article describes the SRI24 atlas, a new standard reference system of normal human brain anatomy, that was created using template-free population registration of high-resolution magnetic resonance images acquired at 3T in a group of 24 normal control subjects. The atlas comprises anatomical channels (T1, T2, and proton density weighted), diffusion-related channels (fractional anisotropy, mean diffusivity, longitudinal diffusivity, mean diffusion-weighted image), tissue channels (CSF probability, gray matter probability, white matter probability, tissue labels), and two cortical parcellation maps. The SRI24 atlas enables multichannel atlas-to-subject image registration. It is uniquely versatile in that it is equally suited for the two fundamentally different atlas applications: label propagation and spatial normalization. Label propagation, herein demonstrated using diffusion tensor image fiber tracking, is enabled by the increased sharpness of the SRI24 atlas compared with other available atlases. Spatial normalization, herein demonstrated using data from a young-old group comparison study, is enabled by its unbiased average population shape property. For both propagation and normalization, we also report the results of quantitative comparisons with seven other published atlases: Colin27, MNI152, ICBM452 (warp5 and air12), and LPBA40 (SPM5, FLIRT, AIR). Our results suggest that the SRI24 atlas, although based on 3T MR data, allows equally accurate spatial normalization of data acquired at 1.5T as the comparison atlases, all of which are based on 1.5T data. Furthermore, the SRI24 atlas is as suitable for label propagation as the comparison atlases and detailed enough to allow delineation of anatomical structures for this purpose directly in the atlas.

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A population-average MRI-based atlas collection of the rhesus macaque.

Donald G. McLaren, Kristopher J. Kosmatka, Terrance R. Oakes … (2009)

Magnetic resonance imaging (MRI) studies of non-human primates are becoming increasingly common; however, the well-developed voxel-based methodologies used in human studies are not readily applied to non-human primates. In the present study, we create a population-average MRI-based atlas collection for the rhesus macaque (Macaca mulatta) that can be used with common brain mapping packages such as SPM or FSL. In addition to creating a publicly available T1-weighted atlas (http://www.brainmap.wisc.edu/monkey.html), probabilistic tissue classification maps and T2-weighted atlases were also created. Theses atlases are aligned to the MRI volume from the Saleem, K.S. and Logothetis, N.K. (2006) atlas providing an explicit link to histological sections. Additionally, we have created a transform to integrate these atlases with the F99 surface-based atlas in CARET. It is anticipated that these tools will help facilitate voxel-based imaging methodologies in non-human primate species, which in turn may increase our understanding of brain function, development, and evolution.

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Author and article information

Journal

Journal ID (nlm-ta): Front Neuroinform

Journal ID (iso-abbrev): Front Neuroinform

Journal ID (publisher-id): Front. Neuroinform.

Title: Frontiers in Neuroinformatics

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1662-5196

Publication date (Electronic preprint): 20 October 2012

Publication date (Electronic): 06 December 2012

Publication date Collection: 2012

Volume: 6

Electronic Location Identifier: 27

Affiliations

[1] ¹Neuroscience Program, SRI International Menlo Park, CA, USA

[2] ²Oregon National Primate Research Center, Oregon Health & Science University Beaverton, OR, USA

[3] ³Department of Psychiatry and Behavioral Sciences, Stanford University Stanford, CA, USA

[4] ⁴National Primate Research Center and Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine Seattle, WA, USA

Author notes

Edited by: Maryann E. Martone, University of California San Diego, USA

Reviewed by: Maryann E. Martone, University of California San Diego, USA; Mihail Bota, University of Southern California, USA; Graham J. Galloway, The University of Queensland, Australia

*Correspondence: Torsten Rohlfing, Neuroscience Program, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 94025-3493, USA. e-mail: rohlfing@ 123456ieee.org

Article

DOI: 10.3389/fninf.2012.00027

PMC ID: 3515865

PubMed ID: 23230398

SO-VID: f0ea9ee7-c210-46e5-a29b-b1baaf7322c4

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

History

Date received : 08 August 2012

Date accepted : 09 November 2012

Page count

Figures: 10, Tables: 1, Equations: 0, References: 41, Pages: 15, Words: 6799

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The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

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Karger: Neurology and Neuroscience

Most cited references 28

Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter.

The SRI24 multichannel atlas of normal adult human brain structure.

A population-average MRI-based atlas collection of the rhesus macaque.

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