Evidence map›Paper›PMID 34902547›Full record

ArticleNeuroImage2022

The role of neural flexibility in cognitive aging.

Eleanna Varangis, Weiwei Qi, Yaakov Stern, Seonjoo Lee

Abstract read
In one paragraph

Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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  9. 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.

Eleanna VarangisDepartment of Neurology, Columbia University, New York, NY 10032, USA.
Weiwei QiMental Health Data Science, New York State Psychiatric Institute, 1051 Riverside Drive, Unit 48, New York, NY 10032, USA; Department of Biostatistics, Columbia University, New York, NY 10032, USA.
Yaakov SternDepartment of Neurology, Columbia University, New York, NY 10032, USA; Department of Psychiatry, Columbia University, New York, NY 10032, USA.
Seonjoo LeeMental Health Data Science, New York State Psychiatric Institute, 1051 Riverside Drive, Unit 48, New York, NY 10032, USA; Department of Psychiatry, Columbia University, New York, NY 10032, USA; Department of Biostatistics, Columbia University, New York, NY 10032, USA. Electronic address: sl3670@cumc.columbia.edu.

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
Imaging of Cognition, Learning and Memory in AgingR01AG026158 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 2004 to 2021
$10.9M
Exploring Cognitive Aging Using Refernce Ability Neural NetworksRF1AG038465 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HABECK, CHRISTIAN GEORG, STERN, YAAKOV · 2016 to 2018
$7.6M
Statistical method for neural mechanism mediating and moderating cognitive system in Alzheimer's disease and aging research.R01AG062578 · NIA · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI LEE, SEONJOO · 2020 to 2024
$2.1M
NIA NIH HHS R01 AG026158NIA NIH HHS R01 AG038465NIA NIH HHS R01 AG062578NIA NIH HHS RF1 AG038465
6 · The paper itself

Abstract

Studies assessing relationships between neural and cognitive changes in healthy aging have shown that a variety of aspects of brain structure and function explain a significant portion of the variability in cognitive outcomes throughout adulthood. Many studies assessing relationships between brain function and cognition have utilized time-averaged, or static functional connectivity methods to explore ways in which brain network organization may contribute to aspects of cognitive aging. However, recent studies in this field have suggested that time-varying, or dynamic measures of functional connectivity, which assess changes in functional connectivity over the course of a scan session, may play a stronger role in explaining cognitive outcomes in healthy young adults. Further, both static and dynamic functional connectivity studies suggest that there may be differences in patterns of brain-cognition relationships as a function of whether or not the participant is performing a task during the scan. Thus, the goals of the present study were threefold: (1) assess whether neural flexibility during both resting as well as task-based scans is related to participant age and cognitive performance in a lifespan aging sample, (2) determine whether neural flexibility moderates relationships between age and cognitive performance, and (3) explore differences in neural flexibility between rest and task. Participants in the study were 386 healthy adults between the ages of 20-80 who provided resting state and/or task-based (Matrix Reasoning) functional magnetic resonance imaging (fMRI) scan data as part of their participation in two ongoing studies of cognitive aging. Neural flexibility measures from both resting and task-based scans reflected the number of times each node changed network assignment, and were averaged both across the whole brain (global neural flexibility) as well as within ten somatosensory/cognitive networks. Results showed that neural flexibility was not related to participant age, and that task-based global neural flexibility, as well as task-based neural flexibility in several networks, tended to be negatively related to reaction times during the Matrix Reasoning task, however these effects did not survive strict multiple comparisons correction. Resting state neural flexibility was not significantly related to either participant age or cognitive performance. Additionally, no neural flexibility measures significantly moderated relationships between participant age and cognitive outcomes. Further, neural flexibility differed as a function of scan type, with resting state neural flexibility being significantly greater than task-based neural flexibility. Thus, neural flexibility measures computed during a cognitive task may be more meaningfully related to cognitive performance across the adult lifespan then resting state measures of neural flexibility.

Indexed as

AdultAgedAged, 80 and overBrainBrain MappingCognitionCognitive AgingFemaleHumansLongevityMagnetic Resonance ImagingMaleMiddle AgedNerve NetNeural PathwaysRestCognitive agingDynamic connectivityFluid Reasoning

Identifiers

PMID34902547
PMCPMC9055953

What OpenQuestion holds

Textmetadata
LicenceTDM
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.