Abstract
Background: There exists a need for more sensitive measures capable of detecting subtle cognitive decline due to Alzheimer's disease.
Objective: To advance the literature in Alzheimer’s disease by demonstrating that performance on a cued-Stroop task is impacted by preclinical Alzheimer's disease neuropathology.
Method: Twenty-nine cognitively asymptomatic older adults completed a computerized, cued-Stroop task in which accuracy rates and intraindividual variability in reaction times were the outcomes of interest. Cerebrospinal fluid biomarkers of Aβ42 and tau were measured and participants were then grouped according to a published p-tau/Aβ42 cutoff reflecting risk for Alzheimer’s disease (preclinical Alzheimer's disease = 14; control = 15).
Results: ANOVAs indicated that accuracy rates did not differ between the groups but 4-second delay incongruent color-naming Stroop coefficient of variation reaction times were higher in the preclinical Alzheimer’s disease group compared to the control group, reflecting increased within-person variability. Moreover, partial correlations showed no relationships between cerebrospinal fluid biomarkers and accuracy rates. However, increases in coefficient of variation reaction times correlated with decreased Aβ42 and increases in p-tau and the p-tau/Aβ42 ratio.
Conclusion: Results supported the ability of the computerized, cued-Stroop task to detect subtle Alzheimer’s disease neuropathology using a small cohort of cognitively asymptomatic older adults. The ongoing measurement of cued-Stroop coefficient of variation reaction times has both scientific and clinical utility in preclinical Alzheimer’s disease.
Keywords: Alzheimer's disease, neuropsychology, cognitive neuroscience, Stroop test, biomarkers, intraindividual variability, aging, cognitive decline.
Current Alzheimer Research
Title:Differential Cued-Stroop Performance in Cognitively Asymptomatic Older Adults with Biomarker-Identified Risk for Alzheimer’s Disease: A Pilot Study
Volume: 15 Issue: 9
Author(s): Ryan Van Patten*, Anne M. Fagan and David A.S. Kaufman
Affiliation:
- Department of Psychology, Saint Louis University, St. Louis, MO,United States
Keywords: Alzheimer's disease, neuropsychology, cognitive neuroscience, Stroop test, biomarkers, intraindividual variability, aging, cognitive decline.
Abstract: Background: There exists a need for more sensitive measures capable of detecting subtle cognitive decline due to Alzheimer's disease.
Objective: To advance the literature in Alzheimer’s disease by demonstrating that performance on a cued-Stroop task is impacted by preclinical Alzheimer's disease neuropathology.
Method: Twenty-nine cognitively asymptomatic older adults completed a computerized, cued-Stroop task in which accuracy rates and intraindividual variability in reaction times were the outcomes of interest. Cerebrospinal fluid biomarkers of Aβ42 and tau were measured and participants were then grouped according to a published p-tau/Aβ42 cutoff reflecting risk for Alzheimer’s disease (preclinical Alzheimer's disease = 14; control = 15).
Results: ANOVAs indicated that accuracy rates did not differ between the groups but 4-second delay incongruent color-naming Stroop coefficient of variation reaction times were higher in the preclinical Alzheimer’s disease group compared to the control group, reflecting increased within-person variability. Moreover, partial correlations showed no relationships between cerebrospinal fluid biomarkers and accuracy rates. However, increases in coefficient of variation reaction times correlated with decreased Aβ42 and increases in p-tau and the p-tau/Aβ42 ratio.
Conclusion: Results supported the ability of the computerized, cued-Stroop task to detect subtle Alzheimer’s disease neuropathology using a small cohort of cognitively asymptomatic older adults. The ongoing measurement of cued-Stroop coefficient of variation reaction times has both scientific and clinical utility in preclinical Alzheimer’s disease.
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Cite this article as:
Patten Van Ryan *, Fagan M. Anne and Kaufman A.S. David , Differential Cued-Stroop Performance in Cognitively Asymptomatic Older Adults with Biomarker-Identified Risk for Alzheimer’s Disease: A Pilot Study, Current Alzheimer Research 2018; 15 (9) . https://dx.doi.org/10.2174/1567205015666180404170359
DOI https://dx.doi.org/10.2174/1567205015666180404170359 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
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Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Alzheimer's Disease Drug Development
Alzheimer's disease is a progressive neurodegenerative disorder that affects millions of people worldwide. Despite decades of research, no cure or disease-modifying treatment is available yet. Therefore, the need for developing effective therapies to treat Alzheimer's disease is an urgent matter. This special issue aims to provide a comprehensive overview of ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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