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Evaluate the efficacy and reliability of functional gradients in within‐subject designs

The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain‐general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions betwe...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaolong, Zang, Zhenxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028665/
https://www.ncbi.nlm.nih.gov/pubmed/36661209
http://dx.doi.org/10.1002/hbm.26213
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author Zhang, Xiaolong
Zang, Zhenxiang
author_facet Zhang, Xiaolong
Zang, Zhenxiang
author_sort Zhang, Xiaolong
collection PubMed
description The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain‐general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between‐group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within‐subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting‐state conditions from 145 participants. We found significantly lower within‐network dispersion of visual network (VN) (p = 7.3 × 10(−4)) as well as sensorimotor network (SMN) (p = 1 × 10(−5)) and between‐network dispersion of VN (p = 2.3 × 10(−4)) under EC than EO, while frontoparietal network (p = 9.2 × 10(−4)) showed significantly higher between‐network dispersion during EC than EO. Test–retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within‐network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting‐state conditions, such that this method could be generalized to other within‐subject designs.
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spelling pubmed-100286652023-03-22 Evaluate the efficacy and reliability of functional gradients in within‐subject designs Zhang, Xiaolong Zang, Zhenxiang Hum Brain Mapp Research Articles The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain‐general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between‐group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within‐subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting‐state conditions from 145 participants. We found significantly lower within‐network dispersion of visual network (VN) (p = 7.3 × 10(−4)) as well as sensorimotor network (SMN) (p = 1 × 10(−5)) and between‐network dispersion of VN (p = 2.3 × 10(−4)) under EC than EO, while frontoparietal network (p = 9.2 × 10(−4)) showed significantly higher between‐network dispersion during EC than EO. Test–retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within‐network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting‐state conditions, such that this method could be generalized to other within‐subject designs. John Wiley & Sons, Inc. 2023-01-20 /pmc/articles/PMC10028665/ /pubmed/36661209 http://dx.doi.org/10.1002/hbm.26213 Text en © 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Zhang, Xiaolong
Zang, Zhenxiang
Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title_full Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title_fullStr Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title_full_unstemmed Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title_short Evaluate the efficacy and reliability of functional gradients in within‐subject designs
title_sort evaluate the efficacy and reliability of functional gradients in within‐subject designs
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028665/
https://www.ncbi.nlm.nih.gov/pubmed/36661209
http://dx.doi.org/10.1002/hbm.26213
work_keys_str_mv AT zhangxiaolong evaluatetheefficacyandreliabilityoffunctionalgradientsinwithinsubjectdesigns
AT zangzhenxiang evaluatetheefficacyandreliabilityoffunctionalgradientsinwithinsubjectdesigns