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Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan

Temporally stable patterns of neural coordination among distributed brain regions are crucial for survival. Recently, many studies highlight association between healthy aging and modifications in organization of functional brain networks, across various time-scales. Nonetheless, quantitative charact...

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Autores principales: Sastry, Nisha Chetana, Roy, Dipanjan, Banerjee, Arpan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930636/
https://www.ncbi.nlm.nih.gov/pubmed/35368068
http://dx.doi.org/10.1093/cercor/bhac133
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author Sastry, Nisha Chetana
Roy, Dipanjan
Banerjee, Arpan
author_facet Sastry, Nisha Chetana
Roy, Dipanjan
Banerjee, Arpan
author_sort Sastry, Nisha Chetana
collection PubMed
description Temporally stable patterns of neural coordination among distributed brain regions are crucial for survival. Recently, many studies highlight association between healthy aging and modifications in organization of functional brain networks, across various time-scales. Nonetheless, quantitative characterization of temporal stability of functional brain networks across healthy aging remains unexplored. This study introduces a data-driven unsupervised approach to capture high-dimensional dynamic functional connectivity (dFC) via low-dimensional patterns and subsequent estimation of temporal stability using quantitative metrics. Healthy aging related changes in temporal stability of dFC were characterized across resting-state, movie-viewing, and sensorimotor tasks (SMT) on a large (n = 645) healthy aging dataset (18–88 years). Prominent results reveal that (1) whole-brain temporal dynamics of dFC movie-watching task is closer to resting-state than to SMT with an overall trend of highest temporal stability observed during SMT followed by movie-watching and resting-state, invariant across lifespan aging, (2) in both tasks conditions stability of neurocognitive networks in young adults is higher than older adults, and (3) temporal stability of whole brain resting-state follows a U-shaped curve along lifespan—a pattern shared by sensorimotor network stability indicating their deeper relationship. Overall, the results can be applied generally for studying cohorts of neurological disorders using neuroimaging tools.
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spelling pubmed-99306362023-02-16 Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan Sastry, Nisha Chetana Roy, Dipanjan Banerjee, Arpan Cereb Cortex Original Article Temporally stable patterns of neural coordination among distributed brain regions are crucial for survival. Recently, many studies highlight association between healthy aging and modifications in organization of functional brain networks, across various time-scales. Nonetheless, quantitative characterization of temporal stability of functional brain networks across healthy aging remains unexplored. This study introduces a data-driven unsupervised approach to capture high-dimensional dynamic functional connectivity (dFC) via low-dimensional patterns and subsequent estimation of temporal stability using quantitative metrics. Healthy aging related changes in temporal stability of dFC were characterized across resting-state, movie-viewing, and sensorimotor tasks (SMT) on a large (n = 645) healthy aging dataset (18–88 years). Prominent results reveal that (1) whole-brain temporal dynamics of dFC movie-watching task is closer to resting-state than to SMT with an overall trend of highest temporal stability observed during SMT followed by movie-watching and resting-state, invariant across lifespan aging, (2) in both tasks conditions stability of neurocognitive networks in young adults is higher than older adults, and (3) temporal stability of whole brain resting-state follows a U-shaped curve along lifespan—a pattern shared by sensorimotor network stability indicating their deeper relationship. Overall, the results can be applied generally for studying cohorts of neurological disorders using neuroimaging tools. Oxford University Press 2022-04-04 /pmc/articles/PMC9930636/ /pubmed/35368068 http://dx.doi.org/10.1093/cercor/bhac133 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Sastry, Nisha Chetana
Roy, Dipanjan
Banerjee, Arpan
Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title_full Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title_fullStr Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title_full_unstemmed Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title_short Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
title_sort stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930636/
https://www.ncbi.nlm.nih.gov/pubmed/35368068
http://dx.doi.org/10.1093/cercor/bhac133
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