A digital 3D atlas of the marmoset brain based on multi-modal MRI.

Neuroimage 2018 04 5;169:106-116. Epub 2017 Dec 5.

Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address:

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets.

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Source
https://linkinghub.elsevier.com/retrieve/pii/S10538119173101
Publisher Site
http://dx.doi.org/10.1016/j.neuroimage.2017.12.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856608PMC
April 2018
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