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ShanghaiTech University Knowledge Management System
Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance | |
Gu, Yi1; Guo, Lianghu1 ![]() ![]() ![]() ![]() ![]() ![]() | |
2024-11-01 | |
发表期刊 | EUROPEAN JOURNAL OF NEUROSCIENCE (IF:2.7[JCR-2023],3.2[5-Year]) |
ISSN | 0953-816X |
EISSN | 1460-9568 |
卷号 | 60期号:11 |
发表状态 | 已发表 |
DOI | 10.1111/ejn.16559 |
摘要 | Resting-state functional magnetic resonance imaging (rs-fMRI) and brain functional connectome (we use 'brain connectome' hereafter for simplicity) have advanced our understanding of the ageing brain and age-related changes in cognitive function. Previous studies have investigated the association among brain connectome and age, global cognition, and memory function separately. However, very few have predicted age, overall cognitive functioning and memory performance in a single study to better understand their complex relationship. In this cross-sectional study, we applied an exploratory, data-driven method to investigate the brain connectome markers that could predict ageing, overall cognitive functioning assessed as intelligence quotient (IQ, measured by Wechsler Memory Scale) and memory performance assessed as memory quotient (MQ, measured by Wechsler Memory Scale) in a carefully designed, multicentre, normal ageing cohort (n = 313). Our results showed that brain connectome could predict ageing and IQ, but the association with MQ was weak. We found that the connectivity with orbital frontal cortex was associated with both ageing and IQ. Mediation analysis further showed that the brain connectome mediated the relationship between age and overall cognitive functioning, suggesting a protective brain connectomic mechanism for maintaining normal cognitive functions during healthy ageing. This work may shed light on the potential neural correlates of healthy ageing, overall cognitive functioning and memory performance. |
关键词 | ageing brain connectivity connectome-based predictive modelling intelligence quotient memory quotient resting-state fMRI |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | STI 2030-Major Projects[2022ZD0209000] ; STI[ZJ2018-ZD-012] ; Shanghai Zhangjiang National Innovation Demonstration Zone Special Funds for Major Projects 'Human Brain Research Imaging Equipment Development and Demonstration Application Platform'[JCYJ-SHFY-2022-014] ; Shanghai Pilot Program for Basic Research-Chinese Academy of Science, Shanghai Branch[NMED2021ZD-01-001] ; Open Research Fund Program of National Innovation Center for Advanced Medical Devices[KCXFZ20211020163408012] ; Shenzhen Science and Technology Program[2021B0909050004] ; Special Fund for Science-Technology Innovation Strategy of Guangdong Province[2019-I2M-5-082] ; Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Science (CIFMS)[21PJ1421400] |
WOS研究方向 | Neurosciences & Neurology |
WOS类目 | Neurosciences |
WOS记录号 | WOS:001354093500001 |
出版者 | WILEY |
文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/449074 |
专题 | 生物医学工程学院 生命科学与技术学院 生命科学与技术学院_特聘教授组_张旭组 信息科学与技术学院_硕士生 生物医学工程学院_公共科研平台_智能医学科研平台 生物医学工程学院_PI研究组_王乾组 生物医学工程学院_PI研究组_张寒组 |
通讯作者 | Zhang, Han |
作者单位 | 1.ShanghaiTech Univ, Sch Biomed Engn, 1 Zhongke Rd, Shanghai 201210, Peoples R China 2.Shanghai Brain Intelligence Project Ctr, Shanghai, Peoples R China 3.Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai, Peoples R China 4.Shanghai Jiao Tong Univ, Sch Biomed Engn, Shanghai, Peoples R China 5.Chifeng Univ, Sch Math & Comp Sci, Chifeng, Peoples R China 6.Shanghai United Imaging Healthcare Co Ltd, Shanghai, Peoples R China 7.Zhejiang Univ, Sch Med, Affiliated Hosp 2, Dept Radiol, Hangzhou, Peoples R China 8.Chinese Acad Med Sci, Guangdong Inst Intelligence Sci & Technol, Res Unit Pain Med, Zhuhai, Guangdong, Peoples R China 9.Huashan Hosp, Neurol Surg Dept, Glioma Surg Div, Shanghai, Peoples R China 10.Fudan Univ, Shanghai Med Coll, Shanghai, Peoples R China 11.Fudan Univ, Zhongshan Hosp, Dept Nucl Med, Shanghai, Peoples R China 12.United Imaging Res Inst Innovat Med Equipment, Shenzhen, Peoples R China 13.Chinese Acad Sci, Shenzhen Inst Adv Technol, Paul C Lauterbur Res Ctr Biomed Imaging, Shenzhen, Peoples R China 14.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China 15.ShanghaiTech Univ, State Key Lab Adv Med Mat & Devices, 1 Zhongke Rd, Shanghai 201210, Peoples R China 16.Shanghai Clin Res & Trail Ctr, Shanghai, Peoples R China |
第一作者单位 | 生物医学工程学院 |
通讯作者单位 | 生物医学工程学院; 上海科技大学 |
第一作者的第一单位 | 生物医学工程学院 |
推荐引用方式 GB/T 7714 | Gu, Yi,Guo, Lianghu,Cai, Xinyi,et al. Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance[J]. EUROPEAN JOURNAL OF NEUROSCIENCE,2024,60(11). |
APA | Gu, Yi.,Guo, Lianghu.,Cai, Xinyi.,Yang, Qing.,Sun, Jian.,...&Zhang, Han.(2024).Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance.EUROPEAN JOURNAL OF NEUROSCIENCE,60(11). |
MLA | Gu, Yi,et al."Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance".EUROPEAN JOURNAL OF NEUROSCIENCE 60.11(2024). |
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