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journal article Open Access Dec 26, 2019

Age‐related structural and functional variations in 5,967 individuals across the adult lifespan

Na Luo ORCID Jing Sui ORCID Anees Abrol ORCID Dongdong Lin Jiayu Chen ORCID Victor M. Vergara ORCID Zening Fu ORCID Yuhui Du ORCID Eswar Damaraju Yong Xu ORCID Jessica A. Turner ORCID Vince D. Calhoun
Human Brain Mapping Vol. 41 No. 7 pp. 1725-1737 · Wiley
View at Publisher Save 10.1002/hbm.24905
Abstract
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 middle occipital 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.
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Citations
75
References
Details
Published
Dec 26, 2019
Vol/Issue
41(7)
Pages
1725-1737
License
View
Authors
N
Na Luo

Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences Beijing China; University of Chinese Academy of Sciences Beijing China

J
Jing Sui

Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences Beijing China; University of Chinese Academy of Sciences Beijing China; CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation, Chinese Academy of Sciences Beijing China

A
Anees Abrol

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia

D
Dongdong Lin

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia

J
Jiayu Chen

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia

V
Victor M. Vergara

CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation, Chinese Academy of Sciences Beijing China

Z
Zening Fu

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia

Y
Yuhui Du

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia; School of Computer and Information Technology Shanxi University Taiyuan China

E
Eswar Damaraju

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia

Y
Yong Xu

Department of Psychiatry First Clinical Medical College/ First Hospital of Shanxi Medical University Taiyuan China

J
Jessica A. Turner

Department of Psychology Neuroscience Institute, Georgia State University Atlanta Georgia

V
Vince D. Calhoun

Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia; Department of Psychiatry Yale University, School of Medicine New Haven Connecticut; Department of Psychology, Computer Science Neuroscience Institute, and Physics, Georgia State University Atlanta Georgia; Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia

Funding
National Natural Science Foundation of China Award: 61773380
Beijing Municipal Science and Technology Commission Award: Z181100001518005
Cite This Article
Na Luo, Jing Sui, Anees Abrol, et al. (2019). Age‐related structural and functional variations in 5,967 individuals across the adult lifespan. Human Brain Mapping, 41(7), 1725-1737. https://doi.org/10.1002/hbm.24905
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