TY - GEN
T1 - Alterations of Brain Functional Networks in Older Adults
T2 - 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2020
AU - Ai, Jing
AU - Liu, Tiantian
AU - Wang, Kexin
AU - Yan, Tianyi
AU - Zhang, Jian
AU - Huang, Tianlin
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/17
Y1 - 2020/10/17
N2 - Aging is the fundamental of neurodegeneration and dementia, affecting every organ in the body. With the aggravation of global aging, more and more research is focusing on how brain changes in older adults. This study aimed to uncover the differences in brain functional networks from the perspective of graph theory between young individuals and older individuals. Here, 61 individuals in their 20s and 94 cognitively healthy old individuals in their 70s underwent a resting-state functional magnetic resonance imaging scan. Based on the graph theory method, a functional network was constructed for each participant. Our results revealed that brain functional networks in older adults maintained small-world properties. However other nodal parameters including degree centrality, betweenness centrality, shortest path lengths, local efficiency, nodal efficiency, and cluster coefficients showed significant differences in many nodes (brain regions) between the 2 groups. Moreover, we correlated these nodal parameters with age, exploring 8 brain regions significantly affected with age. 7 out of 8 brain regions including the bilateral superior parietal lobule, bilateral precuneus, right middle cingulate, right inferior parietal lobule and right transverse temporal gyri were distributed in the default mode network. Our findings, based on graph theory, provided evidence for the alteration of the default mode network in older adults from the perspective of the functional network.
AB - Aging is the fundamental of neurodegeneration and dementia, affecting every organ in the body. With the aggravation of global aging, more and more research is focusing on how brain changes in older adults. This study aimed to uncover the differences in brain functional networks from the perspective of graph theory between young individuals and older individuals. Here, 61 individuals in their 20s and 94 cognitively healthy old individuals in their 70s underwent a resting-state functional magnetic resonance imaging scan. Based on the graph theory method, a functional network was constructed for each participant. Our results revealed that brain functional networks in older adults maintained small-world properties. However other nodal parameters including degree centrality, betweenness centrality, shortest path lengths, local efficiency, nodal efficiency, and cluster coefficients showed significant differences in many nodes (brain regions) between the 2 groups. Moreover, we correlated these nodal parameters with age, exploring 8 brain regions significantly affected with age. 7 out of 8 brain regions including the bilateral superior parietal lobule, bilateral precuneus, right middle cingulate, right inferior parietal lobule and right transverse temporal gyri were distributed in the default mode network. Our findings, based on graph theory, provided evidence for the alteration of the default mode network in older adults from the perspective of the functional network.
KW - graph theory
KW - older adults
KW - resting state-fMRI
KW - the default mode network
UR - http://www.scopus.com/inward/record.url?scp=85099601272&partnerID=8YFLogxK
U2 - 10.1109/CISP-BMEI51763.2020.9263643
DO - 10.1109/CISP-BMEI51763.2020.9263643
M3 - Conference contribution
AN - SCOPUS:85099601272
T3 - Proceedings - 2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2020
SP - 372
EP - 377
BT - Proceedings - 2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2020
A2 - Zheng, Qiang
A2 - Zheng, Xiaopeng
A2 - Zhao, Xiangfu
A2 - Yan, Weiqing
A2 - Zhang, Nan
A2 - Wang, Lipo
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 October 2020 through 19 October 2020
ER -