How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method

被引:0
|
作者
Du, Yuhui [1 ]
Guo, Yating [1 ]
Calhoun, Vince D. [2 ]
机构
[1] Shanxi Univ, Sch Comp & Informat Technol, Taiyuan, Peoples R China
[2] Emory Univ, Georgia State Univ, Georgia Inst Technol, Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30322 USA
基金
中国国家自然科学基金;
关键词
OLDER-ADULTS; AGE; DEFAULT;
D O I
10.1109/EMBC40787.2023.10340189
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many studies have shown that changes in the functional connectivity are diverse along with aging. However, few studies have addressed how aging affects connectivity among large-scale brain networks, and it is challenging to examine gradual aging trajectories from middle adulthood to old age. In this work, based on large-sample fMRI data from 6300 subjects aged between 49 to 73 years, we apply an independent component analysis-based method called NeuroMark to extract brain functional networks and their connectivity (i.e., functional network connectivity (FNC)), and then propose a two-level statistical analysis method to explore robust aging-related changes in functional network connectivity. We found that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network and cerebellum. Our results emphasize the diversity of brain aging and provide new evidence for non-pathological aging of the whole brain.
引用
收藏
页数:4
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