Structural Brain Network Changes across the Adult Lifespan.

Ke Liu,Li Yao,Shixiu Yao,Jiacai Zhang,Kewei Chen,Ke Li,Xiaojuan Guo,Zhen Jin

doi:10.3389/fnagi.2017.00275

Abstract

A number of magnetic resonance imaging (MRI) studies have shown age-related alterations in brain structural networks in different age groups. However, the specific age-associated changes in brain structural networks across the adult lifespan is underexplored. In the current study, we performed a multivariate independent component analysis (ICA) to identify structural brain networks based on covariant gray matter volume and then investigated the age-related trajectories of structural networks over the adult lifespan in 536 healthy subjects aged 20–86 years. Twenty independent components (ICs) were extracted in the ICA, and statistical analyses between age and ICA weights revealed 16 age-related ICs across the adult lifespan. Most of the trajectories of ICA weights demonstrated significant linear decline tendencies, and the corresponding structural networks primarily included the anterior and posterior dorsal attention networks, the ventral and posterior default mode networks, the auditory network, five cerebellum networks and the hippocampus-related network with the most significant decreased tendency among all ICs (p of age = 1.11E-77). Only the temporal lobe-related network showed a significant quadratic tendency with age (p of age2 = 5.66E-06). Our findings not only provide insight into the patterns of the age-related changes of structural networks but also provide a foundation for understanding abnormal aging.

Highlights

Magnetic resonance imaging (MRI) studies have shown that the brain undergoes remarkable structural development during childhood and adolescence and that those alterations continue even through adulthood (Good et al, 2001; Gogtay et al, 2004; Raji et al, 2012; Fjell et al, 2013; Mills et al, 2014)
The Bayesian Information Criterion (BIC) and T-test revealed 16 independent components (ICs) significantly associated with age at Bonferroni corrected P-value (Figures 1–3)
Our current results showed that gray matter volumes of IC 2 and IC 7 exhibited significant linearly decreased trends with age (p = 1.36E-34 and p = 2.40E-13, respectively), which suggested that functional and structural dorsal attention networks (DAN) have similar age-related patterns

Summary

Introduction

Magnetic resonance imaging (MRI) studies have shown that the brain undergoes remarkable structural development during childhood and adolescence and that those alterations continue even through adulthood (Good et al, 2001; Gogtay et al, 2004; Raji et al, 2012; Fjell et al, 2013; Mills et al, 2014). Brickman et al identified aging-related regional MRI covariance patterns in younger and older groups of healthy adults using a multivariate statistical model called the subprofile scaling model (SSM; Brickman et al, 2007) These studies showed that structural covariance patterns or networks demonstrated different age-related changes among the different age groups (Brickman et al, 2007; Li et al, 2013; Hafkemeijer et al, 2014). The age-related trajectories of the brain structural networks across the adult lifespan need to be further explored

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