Evidence map›Paper›PMID 35711905›Full record

ReviewFrontiers in aging neuroscience2022

Cognitive Reserve and Related Constructs: A Unified Framework Across Cognitive and Brain Dimensions of Aging.

William S Kremen, Jeremy A Elman, Matthew S Panizzon, Graham M L Eglit, Mark Sanderson-Cimino, McKenna E Williams, Michael J Lyons, Carol E Franz

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
7.8field-weighted citation impact, top 2% of its field
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

46 citing papers in PubMed, 57 citations in OpenAlex.

  1. Article
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  4. Review
  5. Neuropathology in a diverse cohort of oldest-old: The LifeAfter90 study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
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  15. Review
  16. Article
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  18. A lifespan perspective on cognitive reserve and risk for dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  19. Article
  20. 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

8 authors at 4 institutions in 1 country.

William S KremenDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Jeremy A ElmanDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Matthew S PanizzonDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Graham M L EglitDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Mark Sanderson-CiminoDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
McKenna E WilliamsDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
Michael J LyonsDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, United States.
Carol E FranzDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, United States.
University of California, San Diego · USBoston University · USSan Diego State University · USVA San Diego Healthcare System · US

Funding

The VETSA Longitudinal Twin Study of Cognition and Aging (VETSA 4)R01AG050595 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A, FRANZ, CAROL ELAINE · 2015 to 2024
$28.0M
The VETSA Longitudinal MRI Twin Study of AgingR01AG022381 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2003 to 2019
$22.3M
UC San Diego Clinical and Translational Research InstituteKL2TR001444 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DEPP, COLIN A. · 2015 to 2024
$15.4M
Urban Air Pollution and Pathological Brain Aging: A Nationwide Twin Study in MenP01AG055367 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MACK, WILLIAM J · 2018 to 2022
$11.5M
The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7M
Genetic Predictors, Transcriptomic Biomarkers, & Neurobiological Signatures of Resilience to Alzheimer's DiseaseR01AG064955 · NIA · UPSTATE MEDICAL UNIVERSITY · PI FENNEMA-NOTESTINE, CHRISTINE, GLATT, STEPHEN J · 2019 to 2023
$3.8M
Moderate alcohol use: risk or protective factor for age-related cognitive decline, mild cognitive impairment, and brain health in agingR01AG062483 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCEVOY, LINDA KATHLEEN · 2019 to 2021
$1.6M
Linking genetic subtypes of Alzheimer's disease to biological and cognitive heterogeneityK01AG063805 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A · 2021 to 2024
$516k
Practice Effects in Cognitive Aging: Implications for Biomarkers and Early DiagnosisF31AG064834 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SANDERSON-CIMINO, MARK · 2020 to 2021
$78k
NCATS NIH HHS KL2 TR001444NIA NIH HHS F31 AG064834NIA NIH HHS K01 AG063805NIA NIH HHS P01 AG055367NIA NIH HHS R01 AG022381NIA NIH HHS R01 AG050595NIA NIH HHS R01 AG062483NIA NIH HHS R01 AG064955NIA NIH HHS R01 AG076838
6 · The paper itself

Abstract

Cognitive reserve and related constructs are valuable for aging-related research, but consistency and clarification of terms is needed as there is still no universally agreed upon nomenclature. We propose a new set of definitions for the concepts of reserve, maintenance, and resilience, and we invoke parallel concepts for each that are applicable to cognition and to brain. Our definitions of reserve and resilience correspond reasonably well to dictionary definitions of these terms. We demonstrate logical/methodological problems that arise from incongruence between commonly used conceptual and operational definitions. In our view, cognitive reserve should be defined conceptually as one's total cognitive resources at a given point in time. IQ and education are examples of common operational definitions (often referred to as proxies) of cognitive reserve. Many researchers define cognitive reserve conceptually as a property that allows for performing better than expected cognitively in the face of aging or pathology. Performing better than expected is demonstrated statistically by interactions in which the moderator is typically IQ or education. The result is an irreconcilable situation in which cognitive reserve is both the moderator and the moderation effect itself. Our proposed nomenclature resolves this logical inconsistency by defining performing better than expected as cognitive resilience. Thus, in our usage, we would test the hypothesis that high cognitive reserve confers greater cognitive resilience. Operational definitions (so-called proxies) should not conflate factors that may influence reserve-such as occupational complexity or engagement in cognitive activities-with cognitive reserve itself. Because resources may be depleted with aging or pathology, one's level of cognitive reserve may change over time and will be dependent on when assessment takes place. Therefore, in addition to cognitive reserve and cognitive resilience, we introduce maintenance of cognitive reserve as a parallel to brain maintenance. If, however, education is the measure of reserve in older adults, it precludes assessing change or maintenance of reserve. Finally, we discuss consideration of resistance as a subcategory of resilience, reverse causation, use of residual scores to assess performing better than expected given some adverse factor, and what constitutes high vs. low cognitive reserve across different studies.

Indexed as

brain resiliencecognitive reserve maintenancecognitive resiliencecurrent reservepeak reservereverse causation

Identifiers

PMID35711905
PMCPMC9196190
OpenAlexW4281776978

What OpenQuestion holds

Textmetadata
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.