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Record W2892072207 · doi:10.1080/20445911.2018.1526178

Spatial learners display enhanced oculomotor performance

2018· article· en· W2892072207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Cognitive Psychology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyCognitive psychologyCognitionEye movementSpatial learningSaccadic maskingSpatial abilityStimulus (psychology)Spatial memorySpatial cognitionWorking memoryNeuroscience

Abstract

fetched live from OpenAlex

Attention is important during navigation processes that rely on a cognitive map, as spatial relationships between environmental landmarks need to be selected, encoded, and learned. Spatial learners navigate using this process of cognitive map formation, which relies on the hippocampus. Conversely, response learners memorise a series of actions to navigate, which relies on the caudate nucleus. The present study aimed to investigate the relationship between spatial learning and oculomotor performance. We tested 23 response learners and 23 spatial learners, as determined by the 4-on-8 virtual maze, on an antisaccade task with a gap and emotional visual stimulus manipulation. Spatial learners displayed decreased saccadic reaction time latencies compared to response learners. Performance cost from the gap manipulation was significantly higher in response learners. These results could represent an attentional practice effect through the use of spatial strategies during navigation or a more global increase in cognitive function amongst spatial learners.

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.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.050
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.076
GPT teacher head0.384
Teacher spread0.308 · 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