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Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach

Cross-sectional versus longitudinal comparisons of age-related change have often revealed differing results. In the current study, we used within-subject task-based fMRI to investigate changes in voxel-based activations and behavioral performance across the life span in the Reference Ability Neural...

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Autores principales: Argiris, Georgette, Stern, Yaakov, Habeck, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354716/
https://www.ncbi.nlm.nih.gov/pubmed/34281979
http://dx.doi.org/10.1523/ENEURO.0273-21.2021
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author Argiris, Georgette
Stern, Yaakov
Habeck, Christian
author_facet Argiris, Georgette
Stern, Yaakov
Habeck, Christian
author_sort Argiris, Georgette
collection PubMed
description Cross-sectional versus longitudinal comparisons of age-related change have often revealed differing results. In the current study, we used within-subject task-based fMRI to investigate changes in voxel-based activations and behavioral performance across the life span in the Reference Ability Neural Network cohort, at both baseline and 5 year follow-up. We analyzed fMRI data from between 127 and 159 participants (20–80 years) on a battery of tests relating to each of four cognitive reference abilities. We applied a Gaussian age kernel to capture continuous change across the life span using a 5 year sliding window centered on each age in our participant sample, with a subsequent division into young, middle, and old age brackets. This method was applied separately to both cross-sectional approximations of change and real longitudinal changes adopting a comparative approach. We then focused on longitudinal measurements of neural change to identify regions expressing peak changes and fluctuations of sign change across our sample. Our results revealed several regions expressing divergence between cross-sectional and longitudinal measurements in each domain and age bracket; behavioral comparisons between measurements showed differences in change curves for all four domains, with processing speed displaying the steepest declines. In the longitudinal change measurement, we found lack of support for age-related frontal increases across analysis types, instead finding more posterior regions displaying peak increases in activation, particularly in the old age bracket. Our findings encourage greater focus on longitudinal measurements of age-related changes, which display appreciable differences from cross-sectional approximations.
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spelling pubmed-83547162021-08-11 Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach Argiris, Georgette Stern, Yaakov Habeck, Christian eNeuro Research Article: Methods/New Tools Cross-sectional versus longitudinal comparisons of age-related change have often revealed differing results. In the current study, we used within-subject task-based fMRI to investigate changes in voxel-based activations and behavioral performance across the life span in the Reference Ability Neural Network cohort, at both baseline and 5 year follow-up. We analyzed fMRI data from between 127 and 159 participants (20–80 years) on a battery of tests relating to each of four cognitive reference abilities. We applied a Gaussian age kernel to capture continuous change across the life span using a 5 year sliding window centered on each age in our participant sample, with a subsequent division into young, middle, and old age brackets. This method was applied separately to both cross-sectional approximations of change and real longitudinal changes adopting a comparative approach. We then focused on longitudinal measurements of neural change to identify regions expressing peak changes and fluctuations of sign change across our sample. Our results revealed several regions expressing divergence between cross-sectional and longitudinal measurements in each domain and age bracket; behavioral comparisons between measurements showed differences in change curves for all four domains, with processing speed displaying the steepest declines. In the longitudinal change measurement, we found lack of support for age-related frontal increases across analysis types, instead finding more posterior regions displaying peak increases in activation, particularly in the old age bracket. Our findings encourage greater focus on longitudinal measurements of age-related changes, which display appreciable differences from cross-sectional approximations. Society for Neuroscience 2021-08-04 /pmc/articles/PMC8354716/ /pubmed/34281979 http://dx.doi.org/10.1523/ENEURO.0273-21.2021 Text en Copyright © 2021 Argiris et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Research Article: Methods/New Tools
Argiris, Georgette
Stern, Yaakov
Habeck, Christian
Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title_full Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title_fullStr Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title_full_unstemmed Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title_short Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach
title_sort quantifying age-related changes in brain and behavior: a longitudinal versus cross-sectional approach
topic Research Article: Methods/New Tools
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354716/
https://www.ncbi.nlm.nih.gov/pubmed/34281979
http://dx.doi.org/10.1523/ENEURO.0273-21.2021
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