There is accumulating evidence that early stage Alzheimer's disease reflects a breakdown in attentional control systems that likely contribute to the changes in memory performance, along with other aspects of cognitive performance. Recent evidence indicates that tasks that place a maximum load on attentional systems are particularly useful in serving as a behavioral biomarker both in discriminating healthy aging from early stage DAT, and are correlated with other biomarkers in non-demented older adults. The proposed research plan will continue to longitudinally follow a set of healthy older adults and individuals in the early stages of the disease process, along with individuals who are at risk due to stroke, to better isolate the contributions of novel attentional control measures, and to investigate the extent to which these individuals respond to memory/attention training techniques. We will have three waves of testing, which will be separated by approximately 1.5 years. Each participant will be tested in a single session for each wave of testing, lasting approximately 2 hours. During each wave, we will continue to administer a small battery (no more than 40 minutes) of executive measures (computation span, Stroop, a retroactive interference exclusion measure, and a short switching task). This will afford the ability to continue to follow these individuals with the same set of measures for which we already have data. In addition to the executive control measures, we will also use experimental procedures to provide estimates of three different targeted components in each wave. These will include measures of (a) controlled and automatic processing via the processing dissociation procedure, (b) components of prospective memory performance, and (c) standard mnemonic manipulations (i.e., repeated testing, expanded retrieval, semantic encoding). We will continue to explore distinct measures of participant variability and the components of reaction time distributions that lead to any change in the observed variability estimates as a potential marker for cognitive changes in healthy aging and early stage DAT. In addition, because of recent evidence that certain personality traits (e.g., conscientiousness and neuroticism) predispose individuals for developing DAT, we will explore the modulatory role of personality characteristics in the cognitive markers, and susceptibility to mnemonic techniques. Moreover, we have recently found that personality characteristics are related to cognitive performance including variability estimates. Finally, the behavioral assays obtained in Project 3 will be correlated with the results from the biomarkers available from other projects and cores (e.g., CSF, PIB, genetics, and volumetric measures of targeted areas) to determine which composite measures afford the best behavioral biomarkers.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
5P01AG003991-29
Application #
8374635
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4)
Project Start
Project End
Budget Start
2012-01-01
Budget End
2012-12-31
Support Year
29
Fiscal Year
2012
Total Cost
$145,133
Indirect Cost
$49,650
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Adel, Tameem; Cohen, Taco; Caan, Matthan et al. (2017) 3D scattering transforms for disease classification in neuroimaging. Neuroimage Clin 14:506-517
Schindler, Suzanne E; Jasielec, Mateusz S; Weng, Hua et al. (2017) Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease. Neurobiol Aging 56:25-32
Zhao, Yue; Raichle, Marcus E; Wen, Jie et al. (2017) In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging. Neuroimage 148:296-304
Su, Yi; Vlassenko, Andrei G; Couture, Lars E et al. (2017) Quantitative hemodynamic PET imaging using image-derived arterial input function and a PET/MR hybrid scanner. J Cereb Blood Flow Metab 37:1435-1446
Deming, Yuetiva; Li, Zeran; Kapoor, Manav et al. (2017) Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. Acta Neuropathol 133:839-856
Day, Gregory S; Lim, Tae Sung; Hassenstab, Jason et al. (2017) Differentiating cognitive impairment due to corticobasal degeneration and Alzheimer disease. Neurology 88:1273-1281
Monsell, Sarah E; Mock, Charles; Fardo, David W et al. (2017) Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology. Alzheimer Dis Assoc Disord 31:232-238
Mez, Jesse; Chung, Jaeyoon; Jun, Gyungah et al. (2017) Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans. Alzheimers Dement 13:119-129
Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda (2017) Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning. Brain Sci 7:
Holth, Jerrah; Patel, Tirth; Holtzman, David M (2017) Sleep in Alzheimer's Disease - Beyond Amyloid. Neurobiol Sleep Circadian Rhythms 2:4-14

Showing the most recent 10 out of 831 publications