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Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform
This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing mem...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742316/ http://dx.doi.org/10.1093/geroni/igaa057.2907 |
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author | Mechanic-Hamilton, Dawn Lydon, Sean Miller, Alexander Halberstadter, Kimberly Lane, Jacqueline Das, Sandhitsu Wolk, David |
author_facet | Mechanic-Hamilton, Dawn Lydon, Sean Miller, Alexander Halberstadter, Kimberly Lane, Jacqueline Das, Sandhitsu Wolk, David |
author_sort | Mechanic-Hamilton, Dawn |
collection | PubMed |
description | This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features, and spatial memory. Participants included 30 older adults with normal cognition. They completed the mCAPP, paper and pencil neuropsychological tests and a subset completed a high-resolution structural MRI. The majority of participants found the difficulty level of the mCAPP game to be “just right”. Accuracy on the mCAPP correlated with performance on memory and executive measures, while speed of performance on the mCAPP correlated with performance on attention and executive function measures. Longer trial duration correlated with measures of the parahippocampal cortex. The relationship of mCAPP variables with molecular biomarkers, at-home and burst testing, and development of additional cognitive measures will also be discussed. |
format | Online Article Text |
id | pubmed-7742316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77423162020-12-21 Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform Mechanic-Hamilton, Dawn Lydon, Sean Miller, Alexander Halberstadter, Kimberly Lane, Jacqueline Das, Sandhitsu Wolk, David Innov Aging Abstracts This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features, and spatial memory. Participants included 30 older adults with normal cognition. They completed the mCAPP, paper and pencil neuropsychological tests and a subset completed a high-resolution structural MRI. The majority of participants found the difficulty level of the mCAPP game to be “just right”. Accuracy on the mCAPP correlated with performance on memory and executive measures, while speed of performance on the mCAPP correlated with performance on attention and executive function measures. Longer trial duration correlated with measures of the parahippocampal cortex. The relationship of mCAPP variables with molecular biomarkers, at-home and burst testing, and development of additional cognitive measures will also be discussed. Oxford University Press 2020-12-16 /pmc/articles/PMC7742316/ http://dx.doi.org/10.1093/geroni/igaa057.2907 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Mechanic-Hamilton, Dawn Lydon, Sean Miller, Alexander Halberstadter, Kimberly Lane, Jacqueline Das, Sandhitsu Wolk, David Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title | Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title_full | Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title_fullStr | Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title_full_unstemmed | Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title_short | Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform |
title_sort | detection of alzheimer’s disease-related cognitive change with the mobile cognitive app performance platform |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742316/ http://dx.doi.org/10.1093/geroni/igaa057.2907 |
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