Population-averaged standard template brain atlas for the common marmoset (Callithrix jacchus)
Advanced magnetic resonance (MR) neuroimaging analysis techniques based on voxel-wise statistics, such as voxel-based morphometry (VBM) and functional MRI, are widely applied to cognitive brain research in both human subjects and in non-human primates. Recent developments in imaging have enabled the...
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Published in | NeuroImage (Orlando, Fla.) Vol. 54; no. 4; pp. 2741 - 2749 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
14.02.2011
Elsevier Limited |
Subjects | |
Online Access | Get full text |
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Summary: | Advanced magnetic resonance (MR) neuroimaging analysis techniques based on voxel-wise statistics, such as voxel-based morphometry (VBM) and functional MRI, are widely applied to cognitive brain research in both human subjects and in non-human primates. Recent developments in imaging have enabled the evaluation of smaller animal models with sufficient spatial resolution. The common marmoset (Callithrix jacchus), a small New World primate species, has been widely used in neuroscience research, to which voxel-wise statistics could be extended with a species-specific brain template. Here, we report, for the first time, a tissue-segmented, population-averaged standard template of the common marmoset brain. This template was created by using anatomical T1-weighted images from 22 adult marmosets with a high-resolution isotropic voxel size of (0.2mm)3 at 7-Tesla and DARTEL algorithm in SPM8. Whole brain templates are available at International Neuroinformatics Japan Node website, http://brainatlas.brain.riken.jp/marmoset/.
►A population-averaged brain template for the common marmoset was created. ►Tissue segmented templates would contribute to precise voxel-wise statistics. ►Templates for male, female and those mixed are available at website. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1053-8119 1095-9572 1095-9572 |
DOI: | 10.1016/j.neuroimage.2010.10.061 |