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Two-dimensional horizontal visibility graph analysis of human brain aging on gray matter |
| Huang-Jing Ni(倪黄晶)1,2, Ruo-Yu Du(杜若瑜)1,2, Lei Liang(梁磊)1, Ling-Ling Hua(花玲玲)3, Li-Hua Zhu(朱丽华)4, and Jiao-Long Qin(秦姣龙)5,† |
1 School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
2 Smart Health Big Data Analysis and Location Services Engineering Laboratory of Jiangsu Province, Nanjing 210003, China;
3 Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China;
4 Jiangsu Health Vocational College, Nanjing 211800, China;
5 School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China |
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Abstract Characterizing the trajectory of the healthy aging brain and exploring age-related structural changes in the brain can help deepen our understanding of the mechanism of brain aging. Currently, most structural magnetic resonance imaging literature explores brain aging merely from the perspective of morphological features, which cannot fully utilize the gray-scale values containing important intrinsic information about brain structure. In this study, we propose the construction of two-dimensional horizontal visibility graphs based on the pixel intensity values of the gray matter slices directly. Normalized network structure entropy (NNSE) is then introduced to quantify the overall heterogeneities of these graphs. The results demonstrate a decrease in the NNSEs of gray matter with age. Compared with the middle-aged and the elderly, the larger values of the NNSE in the younger group may indicate more homogeneous network structures, smaller differences in importance between nodes and thus a more powerful ability to tolerate intrusion. In addition, the hub nodes of different adult age groups are primarily located in the precuneus, cingulate gyrus, superior temporal gyrus, inferior temporal gyrus, parahippocampal gyrus, insula, precentral gyrus and postcentral gyrus. Our study can provide a new perspective for understanding and exploring the structural mechanism of brain aging.
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Received: 11 November 2022
Revised: 14 January 2023
Accepted manuscript online: 28 March 2023
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PACS:
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87.18.-h
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(Biological complexity)
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87.57.-s
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(Medical imaging)
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87.61.-c
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(Magnetic resonance imaging)
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87.85.D-
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(Applied neuroscience)
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| Fund: Project supported by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20190736); the Young Scientists Fund of the National Natural Science Foundation of China (Grant Nos. 81701346 and 61603198); and Qinglan Team of Universities in Jiangsu Province (Jiangsu Teacher Letter[2020] 10 and Jiangsu Teacher Letter[2021] 11). |
Corresponding Authors:
Jiao-Long Qin
E-mail: jiaolongq@njust.edu.cn
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Cite this article:
Huang-Jing Ni(倪黄晶), Ruo-Yu Du(杜若瑜), Lei Liang(梁磊), Ling-Ling Hua(花玲玲), Li-Hua Zhu(朱丽华), and Jiao-Long Qin(秦姣龙) Two-dimensional horizontal visibility graph analysis of human brain aging on gray matter 2023 Chin. Phys. B 32 078501
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