Cited by 217Functional Brain Connectivity StudiesDementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Resting-state BOLD networks versus task-associated functional MRI for distinguishing Alzheimer's disease risk groups

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Fleisher, Adam S., Sherzai, Ayesha, Taylor, Curtis, Langbaum, Jessica B.S., Chen, Kewei, Buxton, Richard B.·2009·NeuroImage

Abstract

To assess the ability of resting-state functional magnetic resonance imaging to distinguish known risk factors for AD, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the apolipoprotein e4 allele compared to 12 individuals who were not carriers of the APOE4 gene and did not have a family history of AD. Blood oxygen level dependent fMRI was performed evaluating encoding-associated signal and resting-state default mode network signal differences between the two risk groups. Neurocognitive testing revealed that the high risk group performed worse on category fluency testing, but the groups were equivalent on all other cognitive measures. During encoding of novel face-name pairs, there were no regions of encoding-associated BOLD activations that were different in the high risk group. Encoding-associated deactivations were greater in magnitude in the low risk group in the medial and right lateral parietal cortex, similar to findings in AD studies. The resting-state DMN analysis demonstrated nine regions in the prefrontal, orbital frontal, temporal and parietal lobes that distinguished the two risk groups. Resting-state DMN analysis could distinguish risk groups with an effect size of 3.35, compared to an effect size of 1.39 using encoding-associated fMRI techniques. Imaging of the resting state avoids performance related variability seen in activation fMRI, is less complicated to acquire and standardize, does not require radio-isotopes, and may be more effective at identifying functional pathology associated with AD risk compared to non-resting fMRI techniques.

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Crossref · 10.1016/j.neuroimage.2009.06.021

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References 100 · Cited by 217

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Authors
Fleisher, A. S., Sherzai, A., Taylor, C., Langbaum, J. B. S., Chen, K., & Buxton, R. B.
Affiliations
  • University of California San Diego (US)
  • Loma Linda University Medical Center (US)
  • Banner Alzheimer’s Institute (US)
Corresponding author
Fleisher, Adam S.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2009-10
Volume
47
Issue
4
Pages
1678-1690
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2062843923
Cited by
217
References
100
Citations by year
2026: 2 · 2025: 1 · 2024: 5 · 2023: 5 · 2022: 5 · 2021: 8 · 2020: 10 · 2019: 14 · 2018: 12 · 2017: 12 · 2016: 11 · 2015: 16 · 2014: 23 · 2013: 30 · 2012: 19
FWCI
10.05
Type
journal article
Language
en
Open access
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health
  • National Institute on Aging (K23AG024062)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
Alzheimer's disease risk, resting-state fMRI, default mode network, APOE ε4, family history of Alzheimer's disease, semantic fluency, prefrontal cortex, parietal cortex
MeSH terms
Aged, Algorithms, Alzheimer Disease, Diagnosis, Differential, Evoked Potentials, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Rest, Risk Factors, Sensitivity and Specificity, Task Performance and Analysis, Reproducibility of Results, Risk Assessment

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