4.7 Article

Brain network alterations in Alzheimer's disease measured by Eigenvector centrality in fMRI are related to cognition and CSF biomarkers

期刊

HUMAN BRAIN MAPPING
卷 35, 期 5, 页码 2383-2393

出版社

WILEY-BLACKWELL
DOI: 10.1002/hbm.22335

关键词

amyloid-beta; cognition; resting-state fMRI; Alzheimer's disease; functional connectivity

资金

  1. Research of the VUmc Alzheimer center is part of the neurodegeneration research program of the Neuroscience Campus Amsterdam
  2. Alzheimer Nederland and Stichting VUmc fonds
  3. Stichting Dioraphte
  4. Dutch MS Research Foundation [08-650]
  5. American Health Assistance Foundation
  6. Alzheimer Association
  7. Internationale Stichting Alzheimer Onderzoek
  8. Center of Translational Molecular Medicine
  9. Dutch Organization for Scientific research (NWO)
  10. De Hersenstichting Nederland

向作者/读者索取更多资源

Recent imaging studies have demonstrated functional brain network changes in patients with Alzheimer's disease (AD). Eigenvector centrality (EC) is a graph analytical measure that identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. This study used voxel-wise EC mapping (ECM) to analyze individual whole-brain resting-state functional magnetic resonance imaging (MRI) scans in 39 AD patients (age 67 +/- 8) and 43 healthy controls (age 69 +/- 7). Between-group differences were assessed by a permutation-based method. Associations of EC with biomarkers for AD pathology in cerebrospinal fluid (CSF) and Mini Mental State Examination (MMSE) scores were assessed using Spearman correlation analysis. Decreased EC was found bilaterally in the occipital cortex in AD patients compared to controls. Regions of increased EC were identified in the anterior cingulate and paracingulate gyrus. Across groups, frontal and occipital EC changes were associated with pathological concentrations of CSF biomarkers and with cognition. In controls, decreased EC values in the occipital regions were related to lower MMSE scores. Our main finding is that ECM, a hypothesis-free and computationally efficient analysis method of functional MRI (fMRI) data, identifies changes in brain network organization in AD patients that are related to cognition and underlying AD pathology. The relation between AD-like EC changes and cognitive performance suggests that resting-state fMRI measured EC is a potential marker of disease severity for AD. Hum Brain Mapp 35:2383-2393, 2014. (c) 2013 Wiley Periodicals, Inc.

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