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Record W2018194171 · doi:10.1007/s13670-012-0014-5

Biomarkers of Cognitive Training Effects in Aging

2012· article· en· W2018194171 on OpenAlexaff
Sylvie Belleville, Louis Bherer

Bibliographic record

VenueCurrent Translational Geriatrics and Experimental Gerontology Reports · 2012
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversité du Québec à MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsMedicineCognitionNeurologyCognitive declineCognitive trainingEffects of sleep deprivation on cognitive performanceBrain agingPositron emission tomographyNeuroimagingAging brainNeuropsychologyWhite matterNeurosciencePsychologyPhysical medicine and rehabilitationDiseaseDementiaInternal medicineMagnetic resonance imaging

Abstract

fetched live from OpenAlex

An increasing number of studies have relied on brain imaging to assess the effects of cognitive training in healthy aging populations and in persons with early Alzheimer's disease or mild cognitive impairment (MCI). At the structural level, cognitive training in healthy aging individuals has been associated with increased brain volume, cortical thickness, and density and coherence of white matter tracts. At the functional level, task-related brain activation (using fMRI and PET) and fluorodeoxyglucose positron emission tomography (FDG-PET) were found to be sensitive to the effects of training. In persons with MCI, cognitive training increased brain metabolism and task-related brain activation, whereas healthy older adults showed patterns of increased and decreased activation. Further studies are required to generalize these findings to larger groups and to investigate more diverse training protocols. Research will also need to address important methodological issues regarding the use of biomarkers in cognitive aging, including reliability, clinical validity, and relevance to the pathophysiological process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.374
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations93
Published2012
Admission routes1
Has abstractyes

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Same venueCurrent Translational Geriatrics and Experimental Gerontology ReportsSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207