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 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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Publication Details

Journal
eLife
Published
2025-03-26
DOI
https://doi.org/10.7554/elife.78076
Citations
2
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
2.86

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article

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

Emily J. Van Etten, Noam Alperin, Gene E. Alexander, Tatjana Rundek et al.
2 citations
eLife
Functional Brain Connectivity Studies
2.86
article

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

Emily J. Van Etten, Noam Alperin, Gene E. Alexander, Tatjana Rundek, Kristina Visscher, David A. Raichlen, Sara A. Nolin, PK Bharadwaj, Courtney J Jessup, Mary E Faulkner, Adam J. Woods, Leland L. Fleming, David Geldmacher, Eric C. Porges, Mary Kate Franchetti, Lloyd J. Edwards, Roxanne F Rezaei, Bonnie Levin, Theodore P. Trouard, Virginia G. Wadley, Ron Cohen, Georg A. Hishaw, Stacy Merritt, Paul Stewart
article en
2 citations

Abstract

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.

eLifeVol. 14
University of Southern California (US), University of Arizona (US), University of Miami (US), California Southern University (US), University of Alabama at Birmingham (US), University of Florida (US)
Evelyn F. McKnight Brain Research Foundation
Quality Education
Openalex Percentile: Top 11%
Functional Brain Connectivity Studies
2.86
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