Literature DB >> 19539034

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

Adam S Fleisher1, Ayesha Sherzai, Curtis Taylor, Jessica B S Langbaum, Kewei Chen, Richard B Buxton.   

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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Year:  2009        PMID: 19539034      PMCID: PMC2722694          DOI: 10.1016/j.neuroimage.2009.06.021

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  82 in total

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