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Identifying individual brain development using multimodality brain network
被引:0
|作者:
Jiang, Yuwei
[1
,2
]
Mu, Yangjiayi
[1
,2
]
Xu, Zhao
[1
,2
]
Liu, Qingyang
[1
,2
]
Wang, Shouyan
[1
,2
]
Wang, He
[1
,2
]
Feng, Jianfeng
[1
,2
]
机构:
[1] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China
[2] Fudan Univ, Key Lab Computat Neurosci & Brain Inspired Intelli, Minist Educ, Shanghai, Peoples R China
基金:
国家重点研发计划;
关键词:
FUNCTIONAL CONNECTIVITY;
LONGITUDINAL CHANGES;
SEVERITY;
STABILIZATION;
ASSOCIATION;
DEPRESSION;
PATTERNS;
CHILDREN;
ADHD;
AGE;
D O I:
10.1038/s42003-024-06876-1
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
The cortical development of our brains is in a hierarchical manner and promotes the emergence of large-scale functional hierarchy. However, under interindividual heterogenicity, how the spatiotemporal features of brain networks reflect brain development and mental health remains unclear. Here we collect both resting-state electroencephalography and functional magnetic resonance imaging data from the Child Mind Institute Biobank to demonstrate that during brain growth, the global dynamic patterns of brain states become more active and the dominant networks shift from sensory to higher-level networks; the individual functional network patterns become more similar to that of adults and their spatial coupling tends to be invariable. Furthermore, the properties of multimodality brain networks are sufficiently robust to identify healthy brain age and mental disorders at specific ages. Therefore, multimodality brain networks provide new insights into the functional development of the brain and a more reliable and reasonable approach for age prediction and individual diagnosis. Multimodality brain networks using EEG and fMRI reveal functional development of brain in spatio-temporal domains and help us make a more robust assessment of brain age and mental health.
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页数:13
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