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A Diffusion Tensor MRI Atlas of the Postmortem Rhesus Macaque Brain

1Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, NC, USA.
2Harlow Center for Biological Psychology, University of Wisconsin, Madison, WI, USA.
3Department of Computer Science, Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
Elsevier Science
Publication Date:
Volume Number:
Neuroimage. 2015 Aug 15;117:408-16.
PubMed ID:
Appears in Collections:
K01 AG041211/AG/NIA NIH HHS/United States
P41 EB015897/EB/NIBIB NIH HHS/United States
R01 MH091645/MH/NIMH NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
U54 HD079124/HD/NICHD NIH HHS/United States
Generated Citation:
Calabrese E., Badea A., Coe C.L., Lubach G.R., Shi Y., Styner M.A., Johnson G.A. A Diffusion Tensor MRI Atlas of the Postmortem Rhesus Macaque Brain. Neuroimage. 2015 Aug 15;117:408-16. PMID: 26037056. PMCID: PMC4512905.
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The rhesus macaque (Macaca mulatta) is the most widely used nonhuman primate for modeling the structure and function of the brain. Brain atlases, and particularly those based on magnetic resonance imaging (MRI), have become important tools for understanding normal brain structure, and for identifying structural abnormalities resulting from disease states, exposures, and/or aging. Diffusion tensor imaging (DTI)-based MRI brain atlases are widely used in both human and macaque brain imaging studies because of the unique contrasts, quantitative diffusion metrics, and diffusion tractography that they can provide. Previous MRI and DTI atlases of the rhesus brain have been limited by low contrast and/or low spatial resolution imaging. Here we present a microscopic resolution MRI/DTI atlas of the rhesus brain based on 10 postmortem brain specimens. The atlas includes both structural MRI and DTI image data, a detailed three-dimensional segmentation of 241 anatomic structures, diffusion tractography, cortical thickness estimates, and maps of anatomic variability among atlas specimens. This atlas incorporates many useful features from previous work, including anatomic label nomenclature and ontology, data orientation, and stereotaxic reference frame, and further extends prior analyses with the inclusion of high-resolution multi-contrast image data.

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