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Multimodal Image Analysis of Apparent Brain Age Identifies Physical Fitness as Predictor of Brain Maintenance

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@article{58448411359340ae8c8388fea292e64c,
title = "Multimodal Image Analysis of Apparent Brain Age Identifies Physical Fitness as Predictor of Brain Maintenance",
abstract = "Maintaining a youthful brain structure and function throughout life may be the single most important determinant of successful cognitive aging. In this study, we addressed heterogeneity in brain aging by making image-based brain age predictions and relating the brain age prediction gap (BAPG) to cognitive change in aging. Structural, functional, and diffusion MRI scans from 351 participants were used to train and evaluate 5 single-modal and 4 multimodal prediction models, based on 7 regression methods. The models were compared on mean absolute error and whether they were related to physical fitness and cognitive ability, measured both currently and longitudinally, as well as study attrition and years of education. Multimodal prediction models performed at a similar level as single-modal models, and the choice of regression method did not significantly affect the results. Correlation with the BAPG was found for current physical fitness, current cognitive ability, and study attrition. Correlations were also found for retrospective physical fitness, measured 10 years prior to imaging, and slope for cognitive ability during a period of 15 years. The results suggest that maintaining a high physical fitness throughout life contributes to brain maintenance and preserved cognitive ability.",
keywords = "age predictions, brain aging, cognition, multimodal MRI, physical fitness",
author = "Tora Dun{\aa}s and Anders W{\aa}hlin and Lars Nyberg and Carl-Johan Boraxbekk",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com. Copyright: This record is sourced from MEDLINE/PubMed, a database of the U.S. National Library of Medicine",
year = "2021",
month = jun,
day = "10",
doi = "10.1093/cercor/bhab019",
language = "English",
volume = "31",
pages = "3393--3407",
journal = "Cerebral Cortex",
issn = "1047-3211",
publisher = "Oxford University Press",
number = "7",

}

RIS

TY - JOUR

T1 - Multimodal Image Analysis of Apparent Brain Age Identifies Physical Fitness as Predictor of Brain Maintenance

AU - Dunås, Tora

AU - Wåhlin, Anders

AU - Nyberg, Lars

AU - Boraxbekk, Carl-Johan

N1 - Publisher Copyright: © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com. Copyright: This record is sourced from MEDLINE/PubMed, a database of the U.S. National Library of Medicine

PY - 2021/6/10

Y1 - 2021/6/10

N2 - Maintaining a youthful brain structure and function throughout life may be the single most important determinant of successful cognitive aging. In this study, we addressed heterogeneity in brain aging by making image-based brain age predictions and relating the brain age prediction gap (BAPG) to cognitive change in aging. Structural, functional, and diffusion MRI scans from 351 participants were used to train and evaluate 5 single-modal and 4 multimodal prediction models, based on 7 regression methods. The models were compared on mean absolute error and whether they were related to physical fitness and cognitive ability, measured both currently and longitudinally, as well as study attrition and years of education. Multimodal prediction models performed at a similar level as single-modal models, and the choice of regression method did not significantly affect the results. Correlation with the BAPG was found for current physical fitness, current cognitive ability, and study attrition. Correlations were also found for retrospective physical fitness, measured 10 years prior to imaging, and slope for cognitive ability during a period of 15 years. The results suggest that maintaining a high physical fitness throughout life contributes to brain maintenance and preserved cognitive ability.

AB - Maintaining a youthful brain structure and function throughout life may be the single most important determinant of successful cognitive aging. In this study, we addressed heterogeneity in brain aging by making image-based brain age predictions and relating the brain age prediction gap (BAPG) to cognitive change in aging. Structural, functional, and diffusion MRI scans from 351 participants were used to train and evaluate 5 single-modal and 4 multimodal prediction models, based on 7 regression methods. The models were compared on mean absolute error and whether they were related to physical fitness and cognitive ability, measured both currently and longitudinally, as well as study attrition and years of education. Multimodal prediction models performed at a similar level as single-modal models, and the choice of regression method did not significantly affect the results. Correlation with the BAPG was found for current physical fitness, current cognitive ability, and study attrition. Correlations were also found for retrospective physical fitness, measured 10 years prior to imaging, and slope for cognitive ability during a period of 15 years. The results suggest that maintaining a high physical fitness throughout life contributes to brain maintenance and preserved cognitive ability.

KW - age predictions

KW - brain aging

KW - cognition

KW - multimodal MRI

KW - physical fitness

UR - http://www.scopus.com/inward/record.url?scp=85108304334&partnerID=8YFLogxK

U2 - 10.1093/cercor/bhab019

DO - 10.1093/cercor/bhab019

M3 - Journal article

C2 - 33690853

VL - 31

SP - 3393

EP - 3407

JO - Cerebral Cortex

JF - Cerebral Cortex

SN - 1047-3211

IS - 7

M1 - bhab019

ER -

ID: 64126443