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Record W4206386671 · doi:10.1007/s11682-021-00620-7

Having a stimulating lifestyle is associated with maintenance of white matter integrity with age

2022· article· en· W4206386671 on OpenAlexafffund
Gabriel Ducharme‐Laliberté, Samira Mellah, Sylvie Belleville

Bibliographic record

VenueBrain Imaging and Behavior · 2022
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsBell (Canada)Université de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalInstitut Universitaire de Gériatrie de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWhite matterPsychologyWorking memoryNeuropsychologyAssociation (psychology)Cognitive reserveCognitionMagnetic resonance imagingDevelopmental psychologyMedicinePsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

Brain maintenance refers to the fact that some older adults experience few age-related changes in the brain, which helps maintain their cognition. The goal of this study was to assess maintenance of white matter integrity by testing whether reserve proxies, measuring factors associated to a stimulating lifestyle, affect the maintenance of white matter integrity. Another goal was to measure whether maintenance of white matter integrity explains inter-individual differences in working memory (WM). Forty-one cognitively healthy older adults received a structural magnetic resonance imaging (MRI) examination to measure white matter lesions. They completed an n-back WM task with different loads (1- & 2-back), along with a questionnaire on their lifestyle. There was a positive association between age and volume of white matter lesions. This association was no longer found in those with higher scores on reserve proxies. In addition, smaller volumes of white matter lesions were associated with better performance than expected for age in the 1-back WM task. Better WM is associated with the maintenance of white matter integrity in older adults, which in turn is linked to measures reflecting a stimulating lifestyle throughout life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.260
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes2
Has abstractyes

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