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Developments in scalable strategies for detecting early markers of cognitive decline
Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9645320/ https://www.ncbi.nlm.nih.gov/pubmed/36351888 http://dx.doi.org/10.1038/s41398-022-02237-w |
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author | Whelan, Robert Barbey, Florentine M. Cominetti, Marcia R. Gillan, Claire M. Rosická, Anna M. |
author_facet | Whelan, Robert Barbey, Florentine M. Cominetti, Marcia R. Gillan, Claire M. Rosická, Anna M. |
author_sort | Whelan, Robert |
collection | PubMed |
description | Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using ‘gamified’ versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues. |
format | Online Article Text |
id | pubmed-9645320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96453202022-11-14 Developments in scalable strategies for detecting early markers of cognitive decline Whelan, Robert Barbey, Florentine M. Cominetti, Marcia R. Gillan, Claire M. Rosická, Anna M. Transl Psychiatry Review Article Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using ‘gamified’ versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues. Nature Publishing Group UK 2022-11-09 /pmc/articles/PMC9645320/ /pubmed/36351888 http://dx.doi.org/10.1038/s41398-022-02237-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Whelan, Robert Barbey, Florentine M. Cominetti, Marcia R. Gillan, Claire M. Rosická, Anna M. Developments in scalable strategies for detecting early markers of cognitive decline |
title | Developments in scalable strategies for detecting early markers of cognitive decline |
title_full | Developments in scalable strategies for detecting early markers of cognitive decline |
title_fullStr | Developments in scalable strategies for detecting early markers of cognitive decline |
title_full_unstemmed | Developments in scalable strategies for detecting early markers of cognitive decline |
title_short | Developments in scalable strategies for detecting early markers of cognitive decline |
title_sort | developments in scalable strategies for detecting early markers of cognitive decline |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9645320/ https://www.ncbi.nlm.nih.gov/pubmed/36351888 http://dx.doi.org/10.1038/s41398-022-02237-w |
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