Evidence map›Paper›PMID 34281979›Full record

ArticleeNeuro

Quantifying Age-Related Changes in Brain and Behavior: A Longitudinal versus Cross-Sectional Approach.

Georgette Argiris, Yaakov Stern, Christian Habeck

Abstract read
In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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

3 authors.

Georgette ArgirisCognitive Neuroscience Division, Department of Neurology, Columbia University Medical Center, New York, New York 10032.
Yaakov SternCognitive Neuroscience Division, Department of Neurology, Columbia University Medical Center, New York, New York 10032.
Christian HabeckTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York 10032 ch629@cumc.columbia.edu.ORCID 0000-0001-9961-7446

Funding

Exploring Cognitive Aging Using Reference Ability Neural NetworksR01AG038465 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HABECK, CHRISTIAN GEORG, STERN, YAAKOV · 2011 to 2025
$17.0M
NIA NIH HHS R01 AG038465
6 · The paper itself

Abstract

Cross-sectional versus longitudinal comparisons of age-related change have often revealed differing results. In the current study, we used within-subject task-based fMRI to investigate changes in voxel-based activations and behavioral performance across the life span in the Reference Ability Neural Network cohort, at both baseline and 5 year follow-up. We analyzed fMRI data from between 127 and 159 participants (20-80 years) on a battery of tests relating to each of four cognitive reference abilities. We applied a Gaussian age kernel to capture continuous change across the life span using a 5 year sliding window centered on each age in our participant sample, with a subsequent division into young, middle, and old age brackets. This method was applied separately to both cross-sectional approximations of change and real longitudinal changes adopting a comparative approach. We then focused on longitudinal measurements of neural change to identify regions expressing peak changes and fluctuations of sign change across our sample. Our results revealed several regions expressing divergence between cross-sectional and longitudinal measurements in each domain and age bracket; behavioral comparisons between measurements showed differences in change curves for all four domains, with processing speed displaying the steepest declines. In the longitudinal change measurement, we found lack of support for age-related frontal increases across analysis types, instead finding more posterior regions displaying peak increases in activation, particularly in the old age bracket. Our findings encourage greater focus on longitudinal measurements of age-related changes, which display appreciable differences from cross-sectional approximations.

Indexed as

AgingBrainCognitionCross-Sectional StudiesHumansLongitudinal StudiesMagnetic Resonance Imagingcognitive aginglongitudinalreference ability neural networkswithin-subjects fMRI

Identifiers

PMID34281979
PMCPMC8354716

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.