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Age-related structural and functional variations in 5,967 individuals across the adult lifespan
Luo N(罗娜)1,2; Sui J1,2,3; Anees Abrol4; Dongdong Lin4; Jiayu Chen4; Victor M. Vergara4; Zening Fu4; Yuhui Du4,5; Eswar Damaraju4; Yong Xu6; Jessica A. Turner7; Vince D. Calhoun4
Source PublicationHuman Brain Mapping
2019
Issue2020Pages:1-13
Abstract

Exploring brain changes across the human lifespan is becoming an important topic in neuroscience. Though there are multiple studies which investigated the relationship between age and brain imaging, the results are heterogeneous due to small sample sizes and relatively narrow age ranges. Here, based on year-wise estimation of 5,967 subjects from 13 to 72 years old, we aimed to provide a more precise description of adult lifespan variation trajectories of gray matter volume (GMV), structural network correlation (SNC), and functional network connectivity (FNC) using independent component analysis and multivariate linear regression model. Our results revealed the following relationships: (a) GMV linearly declined with age in most regions, while parahippocampus showed an inverted U-shape quadratic relationship with age; SNC presented a U-shape quadratic relationship with age within cerebellum, and inverted
U-shape relationship primarily in the default mode network (DMN) and frontoparietal (FP) related correlation. (b) FNC tended to linearly decrease within resting-state networks (RSNs), especially in the visual network and DMN. Early increase was revealed between RSNs, primarily in FP and DMN, which experienced a decrease at older ages. U-shape relationship was also revealed to compensate for the cognition deficit in attention and subcortical related connectivity at late years. (c) The link between middleoccipital gyrus and insula, as well as precuneus and cerebellum, exhibited similar changing trends between SNC and FNC across the adult lifespan. Collectively, these results highlight the benefit of lifespan study and provide a precise description of age-related regional variation and SNC/FNC changes based on a large dataset.

Keywordadult lifespan, age-related variations, functional network connectivity, independent component analysis, multivariate linear regression model, structural network correlation
Indexed BySCI
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/28379
Collection脑网络组研究中心
Corresponding AuthorSui J
Affiliation1.Chinese Academy of Science
2.University of Chinese Academy of Sciences
3.CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
4.Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia
5.School of Computer and Information Technology, Shanxi University, Taiyuan, China
6.Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
7.Department of Psychology, Neuroscience Institute, Georgia State University, Atlanta, Georgia
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Luo N,Sui J,Anees Abrol,et al. Age-related structural and functional variations in 5,967 individuals across the adult lifespan[J]. Human Brain Mapping,2019(2020):1-13.
APA Luo N.,Sui J.,Anees Abrol.,Dongdong Lin.,Jiayu Chen.,...&Vince D. Calhoun.(2019).Age-related structural and functional variations in 5,967 individuals across the adult lifespan.Human Brain Mapping(2020),1-13.
MLA Luo N,et al."Age-related structural and functional variations in 5,967 individuals across the adult lifespan".Human Brain Mapping .2020(2019):1-13.
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