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Age‐Related Differences of Cortical Topology Across the Adult Lifespan: Evidence From a Multisite MRI Study With 1427 Individuals

聚类系数 网络拓扑 默认模式网络 网络分析 相似性(几何) 计算机科学 聚类分析 认知 模式识别(心理学) 心理学 人工智能 神经科学 物理 量子力学 图像(数学) 操作系统
作者
Yin Wang,Yinghui Zhang,Weihao Zheng,Xia Liu,Ziyang Zhao,Shan Li,Nan Chen,Lin Yang,Lei Fang,Zhijun Yao,Bin Hu
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:57 (2): 434-443 被引量:12
标识
DOI:10.1002/jmri.28318
摘要

Background Healthy aging is usually accompanied by alterations in brain network architecture, influencing information processing and cognitive performance. However, age‐associated coordination patterns of morphological networks and cognitive variation are not well understood. Purpose To investigate the age‐related differences of cortical topology in morphological brain networks from multiple perspectives. Study Type Prospective, observational multisite study. Population A total of 1427 healthy participants (59.1% female, 51.75 ± 19.82 years old) from public datasets. Field Strength/Sequence 1. 5 T / 3 T , T1 ‐weighted magnetization prepared rapid gradient echo ( MP‐RAGE ) sequence. Assessment The multimodal parcellation atlas was used to define regions of interest (ROIs). The Jensen‐Shannon divergence‐based individual morphological networks were constructed by estimating the interregional similarity of cortical thickness distribution. Graph‐theory based global network properties were then calculated, followed by ROI analysis (including global/nodal topological analysis and hub analysis) with statistical tests. Statistical Tests Chi‐square test, Jensen–Shannon divergence‐based similarity measurement, general linear model with false discovery rate correction. Significance was set at P < 0.05. Results The clustering coefficient ( q = 0.016), global efficiency ( q = 0.007), and small‐worldness ( q = 0.006) were significantly negatively quadratic correlated with age. The group‐level hubs of seven age groups were found mainly distributed in default mode network, visual network, salient network, and somatosensory motor network (the sum of these hubs' distribution in each group exceeds 55%). Further ROI‐wise analysis showed significant nodal trajectories of intramodular connectivities. Data Conclusion These results demonstrated the age‐associated reconfiguration of morphological networks. Specifically, network segregation/integration had an inverted U‐shaped relationship with age, which indicated age‐related differences in transmission efficiency. Evidence Level 2 Technical Efficacy Stage 1
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