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

Na Luo, Jing Sui, Anees Abrol, Dongdong Lin, Jiayu Chen, Victor M. Vergara, Zening Fu, Yuhui Du, Eswar Damaraju, Yong Xu, Jessica A. Turner, Vince D. Calhoun

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
JournalHuman Brain Mapping
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Cerebellum
Linear Models
Occipital Lobe
Parietal Lobe
Neurosciences
Neuroimaging
Sample Size
Cognition
Multivariate Analysis
Brain
Gray Matter
Datasets

Keywords

  • adult lifespan
  • age-related variations
  • functional network connectivity
  • independent component analysis
  • multivariate linear regression model
  • structural network correlation

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Cite this

Age-related structural and functional variations in 5,967 individuals across the adult lifespan. / Luo, Na; Sui, Jing; Abrol, Anees; Lin, Dongdong; Chen, Jiayu; Vergara, Victor M.; Fu, Zening; Du, Yuhui; Damaraju, Eswar; Xu, Yong; Turner, Jessica A.; Calhoun, Vince D.

In: Human Brain Mapping, 01.01.2019.

Research output: Contribution to journalArticle

Luo, N, Sui, J, Abrol, A, Lin, D, Chen, J, Vergara, VM, Fu, Z, Du, Y, Damaraju, E, Xu, Y, Turner, JA & Calhoun, VD 2019, 'Age-related structural and functional variations in 5,967 individuals across the adult lifespan', Human Brain Mapping. https://doi.org/10.1002/hbm.24905
Luo, Na ; Sui, Jing ; Abrol, Anees ; Lin, Dongdong ; Chen, Jiayu ; Vergara, Victor M. ; Fu, Zening ; Du, Yuhui ; Damaraju, Eswar ; Xu, Yong ; Turner, Jessica A. ; Calhoun, Vince D. / Age-related structural and functional variations in 5,967 individuals across the adult lifespan. In: Human Brain Mapping. 2019.
@article{3bdc6a91a32e4f08b6f999383e6752b9,
title = "Age-related structural and functional variations in 5,967 individuals across the adult lifespan",
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.",
keywords = "adult lifespan, age-related variations, functional network connectivity, independent component analysis, multivariate linear regression model, structural network correlation",
author = "Na Luo and Jing Sui and Anees Abrol and Dongdong Lin and Jiayu Chen and Vergara, {Victor M.} and Zening Fu and Yuhui Du and Eswar Damaraju and Yong Xu and Turner, {Jessica A.} and Calhoun, {Vince D.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1002/hbm.24905",
language = "English (US)",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley-Liss Inc.",

}

TY - JOUR

T1 - Age-related structural and functional variations in 5,967 individuals across the adult lifespan

AU - Luo, Na

AU - Sui, Jing

AU - Abrol, Anees

AU - Lin, Dongdong

AU - Chen, Jiayu

AU - Vergara, Victor M.

AU - Fu, Zening

AU - Du, Yuhui

AU - Damaraju, Eswar

AU - Xu, Yong

AU - Turner, Jessica A.

AU - Calhoun, Vince D.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - adult lifespan

KW - age-related variations

KW - functional network connectivity

KW - independent component analysis

KW - multivariate linear regression model

KW - structural network correlation

UR - http://www.scopus.com/inward/record.url?scp=85077147198&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85077147198&partnerID=8YFLogxK

U2 - 10.1002/hbm.24905

DO - 10.1002/hbm.24905

M3 - Article

C2 - 31876339

AN - SCOPUS:85077147198

JO - Human Brain Mapping

JF - Human Brain Mapping

SN - 1065-9471

ER -