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Record W2028314076 · doi:10.1080/13825585.2011.553273

Age-related differences in associative memory depend on the types of associations that are formed

2011· article· en· W2028314076 on OpenAlexaff
Angela K. Troyer, Nicole D’souza, Susan Vandermorris, Kelly J. Murphy

Bibliographic record

VenueAging Neuropsychology and Cognition · 2011
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsAssociative propertyPsychologyContent-addressable memoryDissociation (chemistry)RecallAssociation (psychology)Episodic memoryCognitive psychologyWord (group theory)Developmental psychologyCognitionNeuroscienceComputer scienceLinguisticsArtificial intelligenceMathematicsArtificial neural network

Abstract

fetched live from OpenAlex

Building on well-established findings of age-related decline in associative memory, we examined whether the magnitude of age differences depends on the types of associations that are formed. Specifically, because of predominant age-related changes in the hippocampus, we expected to find larger age differences in recognition of between-domain than within-domain associations. Twenty younger and 20 older healthy adults were given two associative recognition tests, using face-name and word-word pairs, that were matched for difficulty level. As hypothesized, a three-way interaction indicated that, relative to item recognition, age differences in associative recognition were greater for between-domain face-name associations than for within-domain word-word associations. This dissociation is consistent with the idea that the hippocampus plays a prominent role in binding information received from distal neocortical regions. The discussion focuses on the roles of recollection and familiarity in supporting associative memory as well as implications for the remediation of age-related memory decline.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.121
GPT teacher head0.294
Teacher spread0.173 · 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
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

Citations34
Published2011
Admission routes1
Has abstractyes

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