Network segregation is associated with processing speed in the cognitively healthy oldest-old

The brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain’s organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization a...

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Main Authors: Sara A Nolin, Mary E Faulkner, Paul Stewart, Leland L Fleming, Stacy Merritt, Roxanne F Rezaei, Pradyumna K Bharadwaj, Mary Kate Franchetti, David A Raichlen, Cortney J Jessup, Lloyd Edwards, G Alex Hishaw, Emily J Van Etten, Theodore P Trouard, David Geldmacher, Virginia G Wadley, Noam Alperin, Eric S Porges, Adam J Woods, Ron A Cohen, Bonnie E Levin, Tatjana Rundek, Gene E Alexander, Kristina M Visscher
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2025-03-01
Series:eLife
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Online Access:https://elifesciences.org/articles/78076
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author Sara A Nolin
Mary E Faulkner
Paul Stewart
Leland L Fleming
Stacy Merritt
Roxanne F Rezaei
Pradyumna K Bharadwaj
Mary Kate Franchetti
David A Raichlen
Cortney J Jessup
Lloyd Edwards
G Alex Hishaw
Emily J Van Etten
Theodore P Trouard
David Geldmacher
Virginia G Wadley
Noam Alperin
Eric S Porges
Adam J Woods
Ron A Cohen
Bonnie E Levin
Tatjana Rundek
Gene E Alexander
Kristina M Visscher
author_facet Sara A Nolin
Mary E Faulkner
Paul Stewart
Leland L Fleming
Stacy Merritt
Roxanne F Rezaei
Pradyumna K Bharadwaj
Mary Kate Franchetti
David A Raichlen
Cortney J Jessup
Lloyd Edwards
G Alex Hishaw
Emily J Van Etten
Theodore P Trouard
David Geldmacher
Virginia G Wadley
Noam Alperin
Eric S Porges
Adam J Woods
Ron A Cohen
Bonnie E Levin
Tatjana Rundek
Gene E Alexander
Kristina M Visscher
author_sort Sara A Nolin
collection DOAJ
description The brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain’s organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization and cognitive function in older adults who have reached oldest-old ages with healthy cognition can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry (MBAR). We found that the segregation of the association system and the individual networks within the association system (the fronto-parietal network , cingulo-opercular network, and default mode network), has strong associations with overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals representing successful cognitive aging.
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spelling doaj-art-67764bab54ce4e71bcf9744c6f2fc1ed2025-08-20T01:53:34ZengeLife Sciences Publications LtdeLife2050-084X2025-03-011410.7554/eLife.78076Network segregation is associated with processing speed in the cognitively healthy oldest-oldSara A Nolin0Mary E Faulkner1Paul Stewart2Leland L Fleming3https://orcid.org/0000-0002-4047-9031Stacy Merritt4Roxanne F Rezaei5Pradyumna K Bharadwaj6Mary Kate Franchetti7David A Raichlen8Cortney J Jessup9Lloyd Edwards10G Alex Hishaw11Emily J Van Etten12Theodore P Trouard13David Geldmacher14Virginia G Wadley15Noam Alperin16Eric S Porges17Adam J Woods18Ron A Cohen19Bonnie E Levin20Tatjana Rundek21Gene E Alexander22Kristina M Visscher23https://orcid.org/0000-0003-0737-4024University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Miami Miller School of Medicine and Evelyn F.McKnight Brain Institute, Miami, United StatesUniversity of Florida and Evelyn F. and William L.McKnight Brain Institute, Gainesville, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Southern California, Los Angeles, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesUniversity of Miami Miller School of Medicine and Evelyn F.McKnight Brain Institute, Miami, United StatesUniversity of Florida and Evelyn F. and William L.McKnight Brain Institute, Gainesville, United StatesUniversity of Florida and Evelyn F. and William L.McKnight Brain Institute, Gainesville, United StatesUniversity of Florida and Evelyn F. and William L.McKnight Brain Institute, Gainesville, United StatesUniversity of Miami Miller School of Medicine and Evelyn F.McKnight Brain Institute, Miami, United StatesUniversity of Miami Miller School of Medicine and Evelyn F.McKnight Brain Institute, Miami, United StatesUniversity of Arizona and Evelyn F. McKnightBrain Institute, Tucson, United StatesUniversity of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain Institute, Birmingham, United StatesThe brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain’s organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization and cognitive function in older adults who have reached oldest-old ages with healthy cognition can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry (MBAR). We found that the segregation of the association system and the individual networks within the association system (the fronto-parietal network , cingulo-opercular network, and default mode network), has strong associations with overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals representing successful cognitive aging.https://elifesciences.org/articles/78076oldest-oldcognitive agingnetwork segregationprocessing speeddedifferentiation
spellingShingle Sara A Nolin
Mary E Faulkner
Paul Stewart
Leland L Fleming
Stacy Merritt
Roxanne F Rezaei
Pradyumna K Bharadwaj
Mary Kate Franchetti
David A Raichlen
Cortney J Jessup
Lloyd Edwards
G Alex Hishaw
Emily J Van Etten
Theodore P Trouard
David Geldmacher
Virginia G Wadley
Noam Alperin
Eric S Porges
Adam J Woods
Ron A Cohen
Bonnie E Levin
Tatjana Rundek
Gene E Alexander
Kristina M Visscher
Network segregation is associated with processing speed in the cognitively healthy oldest-old
eLife
oldest-old
cognitive aging
network segregation
processing speed
dedifferentiation
title Network segregation is associated with processing speed in the cognitively healthy oldest-old
title_full Network segregation is associated with processing speed in the cognitively healthy oldest-old
title_fullStr Network segregation is associated with processing speed in the cognitively healthy oldest-old
title_full_unstemmed Network segregation is associated with processing speed in the cognitively healthy oldest-old
title_short Network segregation is associated with processing speed in the cognitively healthy oldest-old
title_sort network segregation is associated with processing speed in the cognitively healthy oldest old
topic oldest-old
cognitive aging
network segregation
processing speed
dedifferentiation
url https://elifesciences.org/articles/78076
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