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Record W2024032885 · doi:10.1101/lm.41302

Hippocampal Damage and Exploratory Preferences in Rats: Memory for Objects, Places, and Contexts

2002· article· en· W2024032885 on OpenAlexaff
Dave G. Mumby, Stéphane Gaskin, Melissa J. Glenn, Tania E. Schramek, Hugo Lehmann

Bibliographic record

VenueLearning & Memory · 2002
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsConcordia University
Fundersnot available
KeywordsNoveltyHippocampal formationPsychologyPreferenceHippocampusContext (archaeology)Recognition memoryObject (grammar)Cognitive psychologyNeuroscienceMemoriaCognitionArtificial intelligenceSocial psychologyComputer scienceGeography

Abstract

fetched live from OpenAlex

Rats have a natural tendency to spend more time exploring novel objects than familiar objects, and this preference can be used as an index of object recognition. Rats also show an exploratory preference for objects in locations where they have not previously encountered objects (an index of place memory) and for familiar objects in contexts different from those in which the objects were originally encountered (an index of context memory). In this experiment, rats with cytotoxic lesions of the hippocampal formation were tested on all three versions of the novelty-preference paradigm, with a 5-min retention interval between the familiarization and test phases. Rats with sham lesions displayed a novelty preference on all three trial types, whereas the rats with hippocampal lesions displayed a novelty preference on Object trials but did not discriminate between the objects on Place trials or Context trials. The findings indicate that hippocampal damage impairs memory for contextual or spatial aspects of an experience, whereas memory for objects that were part of the same experience are left relatively intact.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.285
Teacher spread0.204 · 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 designBench or experimental
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

Citations718
Published2002
Admission routes1
Has abstractyes

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