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Distributed functional connectivity predicts neuropsychological test performance among older adults

Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late‐life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain‐wide neural basis of the test performance remains unclear. Using the predictive modeling approa...

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Autores principales: Kwak, Seyul, Kim, Hairin, Kim, Hoyoung, Youm, Yoosik, Chey, Jeanyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8193511/
https://www.ncbi.nlm.nih.gov/pubmed/33960591
http://dx.doi.org/10.1002/hbm.25436
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author Kwak, Seyul
Kim, Hairin
Kim, Hoyoung
Youm, Yoosik
Chey, Jeanyung
author_facet Kwak, Seyul
Kim, Hairin
Kim, Hoyoung
Youm, Yoosik
Chey, Jeanyung
author_sort Kwak, Seyul
collection PubMed
description Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late‐life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain‐wide neural basis of the test performance remains unclear. Using the predictive modeling approach, we aimed to identify the optimal combination of functional connectivities that predicts neuropsychological test scores of novel individuals. Resting‐state functional connectivity and neuropsychological tests included in the OASIS‐3 dataset (n = 428) were used to train the predictive models, and the identified models were iteratively applied to the holdout internal test set (n = 216) and external test set (KSHAP, n = 151). We found that the connectivity‐based predicted score tracked the actual behavioral test scores (r = 0.08–0.44). The predictive models utilizing most of the connectivity features showed better accuracy than those composed of focal connectivity features, suggesting that its neural basis is largely distributed across multiple brain systems. The discriminant and clinical validity of the predictive models were further assessed. Our results suggest that late‐life neuropsychological test performance can be formally characterized with distributed connectome‐based predictive models, and further translational evidence is needed when developing theoretically valid and clinically incremental predictive models.
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spelling pubmed-81935112021-06-15 Distributed functional connectivity predicts neuropsychological test performance among older adults Kwak, Seyul Kim, Hairin Kim, Hoyoung Youm, Yoosik Chey, Jeanyung Hum Brain Mapp Research Articles Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late‐life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain‐wide neural basis of the test performance remains unclear. Using the predictive modeling approach, we aimed to identify the optimal combination of functional connectivities that predicts neuropsychological test scores of novel individuals. Resting‐state functional connectivity and neuropsychological tests included in the OASIS‐3 dataset (n = 428) were used to train the predictive models, and the identified models were iteratively applied to the holdout internal test set (n = 216) and external test set (KSHAP, n = 151). We found that the connectivity‐based predicted score tracked the actual behavioral test scores (r = 0.08–0.44). The predictive models utilizing most of the connectivity features showed better accuracy than those composed of focal connectivity features, suggesting that its neural basis is largely distributed across multiple brain systems. The discriminant and clinical validity of the predictive models were further assessed. Our results suggest that late‐life neuropsychological test performance can be formally characterized with distributed connectome‐based predictive models, and further translational evidence is needed when developing theoretically valid and clinically incremental predictive models. John Wiley & Sons, Inc. 2021-05-07 /pmc/articles/PMC8193511/ /pubmed/33960591 http://dx.doi.org/10.1002/hbm.25436 Text en © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Kwak, Seyul
Kim, Hairin
Kim, Hoyoung
Youm, Yoosik
Chey, Jeanyung
Distributed functional connectivity predicts neuropsychological test performance among older adults
title Distributed functional connectivity predicts neuropsychological test performance among older adults
title_full Distributed functional connectivity predicts neuropsychological test performance among older adults
title_fullStr Distributed functional connectivity predicts neuropsychological test performance among older adults
title_full_unstemmed Distributed functional connectivity predicts neuropsychological test performance among older adults
title_short Distributed functional connectivity predicts neuropsychological test performance among older adults
title_sort distributed functional connectivity predicts neuropsychological test performance among older adults
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8193511/
https://www.ncbi.nlm.nih.gov/pubmed/33960591
http://dx.doi.org/10.1002/hbm.25436
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