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Record W2891329418 · doi:10.14336/ad.2017.1223

Age-related Deficits in Recognition Memory are Protocol-Dependent

2018· article· en· W2891329418 on OpenAlexaff
Diano F. Marrone, Elham Satvat, Anuj Patel

Bibliographic record

VenueAging and Disease · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of WaterlooWilfrid Laurier University
Fundersnot available
KeywordsPerirhinal cortexRecognition memoryMemory impairmentNeurosciencePsychologyCognitive neuroscience of visual object recognitionHippocampal formationCognitive psychologyObject (grammar)CognitionComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The perirhinal cortex (PRh) is a critical mediator of recognition memory, and a wealth of evidence points to impairment in PRh function with age. Despite this evidence, age-related deficits in recognition memory are not consistently observed. This may be partially due to the fact that older animals also have well-established deficits in hippocampal function, and many protocols that assess perirhinal function are also sensitive to hippocampal damage. When using one of these protocols, spontaneous object recognition in an open field, we are able to replicate published age-related deficits using pairs of complex objects. However, when using zero-delay object recognition, a task that is more resistant to the influence of changes in hippocampal function, we find no significant age-related differences in recognition memory in the same animals. These data highlight the importance of the protocol used for testing recognition memory, and may place constraints on the role of the PRh in age-related recognition memory impairment as it is typically tested in much of the literature.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.084
GPT teacher head0.318
Teacher spread0.234 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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