The relationship between delay period eye movements and visuospatial memory
Bibliographic record
Abstract
We investigated whether overt shifts of attention were associated with visuospatial memory performance. Participants were required to study the locations of a set of visual objects and subsequently detect changes to the spatial location of one of the objects following a brief delay period. Relational information regarding the locations among all of the objects could be used to support performance on the task (Experiment 1) or relational information was removed during test and location manipulation judgments had to be made for a singly presented target item (Experiment 2). We computed the similarity of the fixation patterns in space during the study phase to the fixations made during the delay period. Greater fixation pattern similarity across participants was associated with higher accuracy when relational information was available at test (Experiment 1); however, this association was not observed when the target item was presented in isolation during the test display (Experiment 2). Similarly, increased fixation pattern similarity on a given trial (within participants) was associated with successful task performance when the relations among studied items could be used for comparison (Experiment 1), but not when memory for absolute spatial location was assessed (Experiment 2). This pattern of behavior and performance on the two tasks suggested that eye movements facilitated memory for the relationships among objects. Shifts of attention through eye movements may provide a mechanism for the maintenance of relational visuospatial memory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".