4.5 Article

Disrupted structural and functional brain networks in Alzheimer's disease

期刊

NEUROBIOLOGY OF AGING
卷 75, 期 -, 页码 71-82

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.neurobiolaging.2018.11.005

关键词

Structural connectivity; Functional connectivity; Small-world; Connectome; Graph theory

资金

  1. Ministry of Science and Technology [2017YFC1311100]
  2. National Natural Science Foundation of China [81620108016, 81601559, 81171018]
  3. Guangdong Provincial Natural Science Foundation of China [2016A030310233]
  4. Changjiang Scholar Professorship Award [T2015027]
  5. Beijing Natural Science Foundation [Z161100004916027, Z151100003915082]
  6. Fundamental Research Funds for the Central Universities [2017XTCX04]

向作者/读者索取更多资源

Studies have demonstrated that the clinical manifestations of Alzheimer's disease (AD) are associated with abnormal connections in either functional connectivity networks (FCNs) or structural connectivity networks (SCNs). However, the FCN and SCN of AD have usually been examined separately, and the results were inconsistent. In this multimodal study, we collected resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging data from 46 patients with AD and 39 matched healthy controls (HCs). Graph-theory analysis was used to investigate the topological organization of the FCN and SCN simultaneously. Compared with HCs, both the FCN and SCN of patients with AD showed disrupted network integration (i.e., increased characteristic path length) and segregation (i.e., decreased intramodular connections in the default mode network). Moreover, the FCN, but not the SCN, exhibited a reduced clustering coefficient and reduced rich club connections in AD. The coupling (i.e., correlation) of the FCN and SCN in AD was increased in connections of the default mode network and the rich club. These findings demonstrated overlapping and distinct network disruptions in the FCN and SCN and a strengthened correlation between FCNs and SCNs in AD, which provides a novel perspective for understanding the pathophysiological mechanisms underlying AD. (C) 2018 Elsevier Inc. All rights reserved.

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