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Record W4246125334 · doi:10.32920/ryerson.14656536

Age-related associative memory deficit: simulation and strategies to improve performance

2021· preprint· en· W4246125334 on OpenAlexaff
Brenda Iok Wong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyRecallEncoding (memory)Cognitive psychologyAssociative propertyCognitionYoung adultDevelopmental psychologyContent-addressable memoryAssociative learningWorking memoryTask (project management)NeuroscienceComputer science

Abstract

fetched live from OpenAlex

According to the associative deficit hypothesis, older adults experience greater difficulty in remembering associations between pieces of information (associative memory) than young adults, despite their relatively intact memory for individual items (item memory). Recent research suggests that this deficit might be related to older adults’ reduced availability of attentional resources – the reservoir of mental energy needed for the operations of cognition functions. The purpose of this Dissertation was to examine the role of attentional resources in associative deficit, and to explore encoding manipulations that might alleviate the deficit in older adults. In Study 1, young adults’ attentional resources during encoding of word pairs were depleted using a divided attention task. These participants showed an associative deficit commonly observed in older adults, and were less likely to use effective encoding strategies and recollection-based processes to support their memory in comparison to young adults under full attention. The resemblance in memory performance between young adults under divided attention and older adults suggests that lack of attentional resources might be a contributing factor in older adults’ associative deficit. In Study 2, participants’ resource load during encoding was reduced by learning individual items and their associations sequentially in two phases. Older adults in this condition showed equivalent memory performance to young adults, and were more likely to use effective encoding strategies and recollection-based processes than older adults in Study 1 who studied items and associations simultaneously. Finally, Study 3 employed a value-directed learning paradigm, in which participants studied high- and low-value word pairs. Older adults showed similar memory performance for both high- and low-value word pairs as young adults, without any signs of associative deficit. Assigning value to associative information might prompt older adults to prioritize associative encoding over item encoding, which benefits their associative memory. Taken together, these results suggest that depletion of attentional resources during encoding could impair associative memory. Furthermore, older adults’ associative deficit could be effectively alleviated with sufficient environmental support during encoding, such as when resource competition between item and associative encoding is minimized (Study 2) or when being guided to prioritize encoding of associations over items (Study 3).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.312
Teacher spread0.269 · 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 designSimulation or modeling
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

Citations0
Published2021
Admission routes1
Has abstractyes

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