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Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals.
Lyu, Wenjiao; Wu, Ye; Huang, Haoming; Chen, Yuna; Tan, Xin; Liang, Yi; Ma, Xiaomeng; Feng, Yue; Wu, Jinjian; Kang, Shangyu; Qiu, Shijun; Yap, Pew-Thian.
Affiliation
  • Lyu W; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Wu Y; Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
  • Huang H; Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
  • Chen Y; School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu China.
  • Tan X; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Liang Y; Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Ma X; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Feng Y; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Wu J; Department of Radiology, Jingzhou First People's Hospital of Hubei Province, Jingzhou, Hubei China.
  • Kang S; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Qiu S; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
  • Yap PT; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.
Cogn Neurodyn ; 17(6): 1525-1539, 2023 Dec.
Article de En | MEDLINE | ID: mdl-37969945
ABSTRACT
An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Cogn Neurodyn Année: 2023 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Cogn Neurodyn Année: 2023 Type de document: Article