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Record W2058727618 · doi:10.1037/a0016566

Evidence of anticipatory eye movements in the spatial Hebb repetition effect: Insights for modeling sequence learning.

2009· article· en· W2058727618 on OpenAlexafffund
Sébastien Tremblay, Jean Saint‐Aubin

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de MonctonUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRepetition (rhetorical device)RecallSequence learningSequence (biology)Eye movementCognitive psychologyMovement (music)PsychologySpeech recognitionTask (project management)Presentation (obstetrics)Serial position effectComputer scienceArtificial intelligenceCommunicationFree recallLinguistics

Abstract

fetched live from OpenAlex

In the present study, the authors offer a window onto the mechanisms that drive the Hebb repetition effect through the analysis of eye movement and recall performance. In a spatial serial recall task in which sequences of dots are to be remembered in order, when one particular series is repeated every 4 trials, memory performance markedly improves over repetitions. This is known as the Hebb repetition effect. Eye movement recorded during the presentation of the to-be-remembered (TBR) information revealed that for the repeated sequence, participants fixated the location of the next TBR location before the actual presentation of the dot. The extent to which a TBR location was anticipated increased over repetition and occurred only for post-initial positions of the repeated sequence. Eye movement-based rehearsal activity was related to recall performance but not to sequence learning. The findings provide further evidence of anticipatory behavior in sequence learning and place key constraints on modeling the Hebb repetition effect.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.222
GPT teacher head0.455
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 teacher head, 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

Citations21
Published2009
Admission routes2
Has abstractyes

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