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Record W4382400566 · doi:10.1051/shsconf/202317101003

Extending the Embodied Simulation Hypothesis: Effects of Motor Simulation in the Mind on Memory Retrieval

2023· article· en· W4382400566 on OpenAlexaff
Ruoqi Li, Qingyang Fu, Yunqi Chen

Bibliographic record

VenueSHS Web of Conferences · 2023
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmbodied cognitionRecallEncoding (memory)Cognitive psychologyComputer scienceCognitive sciencePsychologySimulated realityArtificial intelligence

Abstract

fetched live from OpenAlex

The embodied simulation hypothesis of modality-specific areas activation influencing language processing has matured over time. However, whether the idea can be applied to broader aspects other than language processing, such as memory processing, remains to be investigated. In this study, we extend the embodied simulation hypothesis, looking at the effects of motor simulation in mind, specifically handedness, on long-term memory retrieval. To test our hypothesis, we introduce two lists of Chinese characters as materials for memory and use old/new recognition tasks to measure retrieval performance. Our prediction of the results is that interfering with relevant motor systems (dominant hand) involved in memory encoding during retrieval will impair a person’s ability to recall. If our experimental results support our hypothesis, this not only provides strong evidence for the embodied simulation hypothesis but our research may also be applied to the field of memory, providing potential inspiration for memory enhancement.

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)0.009
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.087
GPT teacher head0.352
Teacher spread0.265 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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