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Record W7154576536 · doi:10.48448/pbgr-a510

Enactment and Embodiment Impact the Recall of Object-Location Associations

2025· other· W7154576536 on OpenAlexaff
Cognitive Science Society 2025, Stefan Kohler, Suesan MacRae, Ken McRae

Bibliographic record

VenueUnderline Science Inc. · 2025
Typeother
Language
Field
Topic
Canadian institutionsWestern University
Fundersnot available
KeywordsRecallEmbodied cognitionAction (physics)Object (grammar)Relevance (law)Context (archaeology)Encoding (memory)Associative propertyAssociation (psychology)

Abstract

fetched live from OpenAlex

The role of self-generated movement in memory retrieval has been demonstrated in enactment paradigms. However, in the context of object-location memory, the impact of action during learning has not yet been investigated, despite the ecological relevance of such behaviors. In the current project, we present new evidence that actively placing an object in a target location during learning leads to more precise, and faster, subsequent recall of the object-location associations than simply observing this placement. We further demonstrate differences in object- location memory depending on the category of stimuli that participants are engaging with by showing that images of objects with high manipulability are placed more precisely, more quickly, and more directly (mouse-tracking) than images of objects with low manipulability. We suggest that these latter differences are due to the motor information implicitly activated during processing of high manipulability items, and reflect the embodied nature of concepts. Although both enactment and manipulability impacted object-location recall, they did not interact. This research extends findings on enactment to associative encoding processes, and informs our understanding of the relationship between enactment and embodiment in human memory.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.334
Teacher spread0.315 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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