Visual working memory as the substrate for mental rotation: A replication
Bibliographic record
Abstract
An experimental study by Hyun and Luck suggests that object working memory, but not spatial working memory, is employed during mental rotation. In contrast, correlational research points to the relevance of spatial working memory in mental rotation. Considering these somewhat conflicting results and the fact that a small sample was acquired in the study of Hyun and Luck, a replication of their study was conducted. Additionally, potential sex effects were explored. We collected (usable) data from 213 individuals across two experiments. All participants performed a mental-rotation task alone, a working-memory task alone, and both tasks concurrently. We expected greater rotation-dependent interference between tasks when the working memory task concerned object features (Experiment 1) than when it concerned spatial locations (Experiment 2). In Experiment 1, dual-task interference was observed in working-memory accuracy. In Experiment 2, there were interference effects in both mental rotation accuracy and working-memory accuracy. However, interference did not differ between experiments. Moreover, interference was not rotation dependent in either of the experiments. Thus, we could not replicate the findings of Hyun and Luck. No sex differences were found in exploratory analyses. The general interference effects found in this study may reflect the involvement of visual working memory in the processing and decision-making stages of the mental rotation of letters. This study underscores the need for further research to fully understand the role of visual working memory in mental rotation, especially with more complex stimuli.
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 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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".