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Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging...

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Detalles Bibliográficos
Autores principales: Lv, Qiming, Yan, Mingchao, Shen, Xiangyu, Wu, Jing, Yu, Wenwen, Yan, Shengyao, Yang, Feng, Zeljic, Kristina, Shi, Yuequan, Zhou, Zuofu, Lv, Longbao, Hu, Xintian, Menon, Ravi, Wang, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7727342/
https://www.ncbi.nlm.nih.gov/pubmed/32844170
http://dx.doi.org/10.1093/cercor/bhaa229
Descripción
Sumario:The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P < 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies.