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Dispersion of functional gradients across the adult lifespan
Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques in neuroimagin...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779368/ https://www.ncbi.nlm.nih.gov/pubmed/32828920 http://dx.doi.org/10.1016/j.neuroimage.2020.117299 |
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author | Bethlehem, Richard A.I. Paquola, Casey Seidlitz, Jakob Ronan, Lisa Bernhardt, Boris Consortium, Cam-CAN Tsvetanov, Kamen A. |
author_facet | Bethlehem, Richard A.I. Paquola, Casey Seidlitz, Jakob Ronan, Lisa Bernhardt, Boris Consortium, Cam-CAN Tsvetanov, Kamen A. |
author_sort | Bethlehem, Richard A.I. |
collection | PubMed |
description | Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques in neuroimaging provides a new means of studying functional organisation in a multi-dimensional connectivity space. Here, we studied ageing and behaviourally-relevant differences in a three-dimensional connectivity space using the Cambridge Centre for Ageing Neuroscience cohort (n = 643). Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within and between functional communities. We detected a strong shift of the visual network across the adult lifespan from an extreme to a more central position in the 3D gradient space. In contrast, the dispersion distance between transmodal communities (dorsal attention, ventral attention, frontoparietal and default mode) did not change. However, these communities themselves were increasingly dispersed with increasing age, reflecting more dissimilar functional connectivity profiles within each community. Increasing dispersion of frontoparietal, attention and default mode networks, in particular, were associated negatively with cognition, measured by fluid intelligence. By using a technique that explicitly captures the ordering of functional systems in a multi-dimensional hierarchical framework, we identified behaviorally-relevant age-related differences of within and between network organisation. We propose that the study of functional gradients across the adult lifespan could provide insights that may facilitate the development of new strategies to maintain cognitive ability across the lifespan in health and disease. |
format | Online Article Text |
id | pubmed-7779368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Academic Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77793682021-01-08 Dispersion of functional gradients across the adult lifespan Bethlehem, Richard A.I. Paquola, Casey Seidlitz, Jakob Ronan, Lisa Bernhardt, Boris Consortium, Cam-CAN Tsvetanov, Kamen A. Neuroimage Article Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques in neuroimaging provides a new means of studying functional organisation in a multi-dimensional connectivity space. Here, we studied ageing and behaviourally-relevant differences in a three-dimensional connectivity space using the Cambridge Centre for Ageing Neuroscience cohort (n = 643). Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within and between functional communities. We detected a strong shift of the visual network across the adult lifespan from an extreme to a more central position in the 3D gradient space. In contrast, the dispersion distance between transmodal communities (dorsal attention, ventral attention, frontoparietal and default mode) did not change. However, these communities themselves were increasingly dispersed with increasing age, reflecting more dissimilar functional connectivity profiles within each community. Increasing dispersion of frontoparietal, attention and default mode networks, in particular, were associated negatively with cognition, measured by fluid intelligence. By using a technique that explicitly captures the ordering of functional systems in a multi-dimensional hierarchical framework, we identified behaviorally-relevant age-related differences of within and between network organisation. We propose that the study of functional gradients across the adult lifespan could provide insights that may facilitate the development of new strategies to maintain cognitive ability across the lifespan in health and disease. Academic Press 2020-11-15 /pmc/articles/PMC7779368/ /pubmed/32828920 http://dx.doi.org/10.1016/j.neuroimage.2020.117299 Text en © 2020 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Bethlehem, Richard A.I. Paquola, Casey Seidlitz, Jakob Ronan, Lisa Bernhardt, Boris Consortium, Cam-CAN Tsvetanov, Kamen A. Dispersion of functional gradients across the adult lifespan |
title | Dispersion of functional gradients across the adult lifespan |
title_full | Dispersion of functional gradients across the adult lifespan |
title_fullStr | Dispersion of functional gradients across the adult lifespan |
title_full_unstemmed | Dispersion of functional gradients across the adult lifespan |
title_short | Dispersion of functional gradients across the adult lifespan |
title_sort | dispersion of functional gradients across the adult lifespan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779368/ https://www.ncbi.nlm.nih.gov/pubmed/32828920 http://dx.doi.org/10.1016/j.neuroimage.2020.117299 |
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