Evidence map›Paper›PMID 39432149›Full record

ArticleGeroScience2025

Profiles of brain topology for dual-functional stability in old age.

Sa Zhou, Mia Anthony, Ehsan Adeli, F Vankee Lin

Abstract read
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sa ZhouDepartment of Psychiatry and Behavioral Sciences, Stanford University, 1070 Arastradero Rd, Palo Alto, CA, 94304, USA. sazhou@stanford.edu.
Mia AnthonyDepartment of Psychiatry and Behavioral Sciences, Stanford University, 1070 Arastradero Rd, Palo Alto, CA, 94304, USA.
Ehsan AdeliDepartment of Psychiatry and Behavioral Sciences, Stanford University, 1070 Arastradero Rd, Palo Alto, CA, 94304, USA.
F Vankee LinDepartment of Psychiatry and Behavioral Sciences, Stanford University, 1070 Arastradero Rd, Palo Alto, CA, 94304, USA.

Funding

Stanford Alzheimer's Disease Research CenterAdmin Supp: Developing iPSC models for AD and PDP30AG066515 · NIA · STANFORD UNIVERSITY · PI Lisa Goldman Rosas · 2020 to 2026
$29.0M
U24 NEW Brain Aging Diversity SupplementU24AG072701 · NIA · UNIVERSITY OF ROCHESTER · PI CONWELL, YEATES, LIN, FENG VANKEE · 2021 to 2024
$2.6M
Applying the Neuroeconomics Paradigm for the Assessment of Central Fatigability in the Aging PopulationR21AG053193 · NIA · UNIVERSITY OF ROCHESTER · PI LIN, FENG VANKEE · 2016 to 2017
$421k
Biotechnology and Biological Sciences Research Council BB/H008217/1NATIONAL INSTITUTE OF AGING NIH AG053193NATIONAL INSTITUTE OF AGING NIH AG072701NIA NIH HHS P30 AG066515NIA NIH HHS R21 AG053193
6 · The paper itself

Abstract

Dual-functional stability (DFS) in cognitive and physical abilities is important for successful aging. This study examines the brain topology profiles that underpin high DFS in older adults by testing two hypotheses: (1) older adults with high DFS would exhibit a unique brain organization that preserves their physical and cognitive functions across various tasks, and (2) any individuals with this distinct brain topology would consistently show high DFS. We analyzed two cohorts of cognitively and physically healthy older adults from the UK (Cam-CAN, n = 79) and the US (CF, n = 48) using neuroimaging data and a combination of cognitive and physical tasks. Variability in DFS was characterized using k-mean clustering for intra-individual variability (IIV) in cognitive and physical tasks. Graph theory analyses of diffusion tensor imaging connectomes were used to assess brain network segregation and integration through clustering coefficients (CCs) and shortest path lengths (PLs). Using support vector machine and regression, brain topology features, derived from PLs + CCs, differentiated the high DFS subgroup from low and mix DFS subgroups with accuracies of 65.82% and 84.78% in Cam-CAN and CF samples, respectively, which predicted cross-task DFS score in CF samples at 58.06% and 70.53% for cognitive and physical stability, respectively. Results showed distinctive neural correlates associated with high DFS, notably varying regional brain segregation and integration within critical areas such as the insula, frontal pole, and temporal pole. The identified brain topology profiles suggest a distinctive neural basis for DFS, a trait indicative of successful aging. These insights offer a foundation for future research to explore targeted interventions that could enhance cognitive and physical resilience in older adults, promoting a healthier and more functional lifespan.

Indexed as

AgingBrainCognitionAgedAged, 80 and overConnectomeDiffusion Tensor ImagingFemaleHumansMaleBrain topologyDiffusion tensor imagingDual-functionalityIntra-individual variabilitySuccessful aging

Identifiers

PMID39432149
PMCPMC11978588

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.