UNC-Emory Infant Atlases for Macaque Brain Image Analysis: Postnatal Brain Development through 12 Months

• Authors: Yundi Shi, University of North Carolina; Francois Budin, Kitware Inc; Eva Yapuncich, University of North Carolina; Ashley Rumple, University of North Carolina; Jeffrey T. Young, University of North Carolina; Christa Payne, Emory University; Xiaodong Zhang, Emory University; Xiaoping Hu, University of California Riverside; Jodi Godfrey, Emory University; Brittany Howell, University of North Carolina; Maria Sanchez, Emory University; Martin A. Styner, University of North Carolina
• Journal Title: Frontiers in Neuroscience
• Volume: Volume 10
• Publisher: Frontiers Media | 2017-01-10, Pages 617-617
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.3389/fnins.2016.00617
• Subjects: Psychology, Behavioral; Psychology, General; Biology, Neuroscience
• Keywords: Science & Technology; Life Sciences & Biomedicine; Neurosciences; Neurosciences & Neurology; neuroimaging; non-human primate; macaque; computational atlases; white matter pathways; magnetic resonance imaging; diffusion tensor imaging; automatic segmentation; MACACA-MULATTA; CEREBRAL-CORTEX; RHESUS MACAQUES; QUALITY-CONTROL; DIFFUSION; SEGMENTATION; TRAJECTORIES; TEMPLATE; CIRCUITS; MRI

Abstract

Computational anatomical atlases have shown to be of immense value in neuroimaging as they provide age appropriate reference spaces alongside ancillary anatomical information for automated analysis such as subcortical structural definitions, cortical parcellations or white fiber tract regions. Standard workflows in neuroimaging necessitate such atlases to be appropriately selected for the subject population of interest. This is especially of importance in early postnatal brain development, where rapid changes in brain shape and appearance render neuroimaging workflows sensitive to the appropriate atlas choice. We present here a set of novel computation atlases for structural MRI and Diffusion Tensor Imaging as crucial resource for the analysis of MRI data from non-human primate rhesus monkey (Macaca mulatta) data in early postnatal brain development. Forty socially-housed infant macaques were scanned longitudinally at ages 2 weeks, 3, 6, and 12 months in order to create cross-sectional structural and DTI atlases via unbiased atlas building at each of these ages. Probabilistic spatial prior definitions for the major tissue classes were trained on each atlas with expert manual segmentations. In this article we present the development and use of these atlases with publicly available tools, as well as the atlases themselves, which are publicly disseminated to the scientific community.