{"title":"Alterations of Brain Functional Networks in Older Adults: A Resting-state fMRI Study Using Graph Theory","authors":"Jing Ai, Tiantian Liu, Kexin Wang, Tianyi Yan, Jian Zhang, Tianlin Huang","doi":"10.1109/CISP-BMEI51763.2020.9263643","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.