Rotational Remapping in Human Spatial Memory during Eye and Head Motion
Bibliographic record
Abstract
The brain uses vision and other senses to compute the locations of objects relative to the body, and then must update these locations when the body moves. How geometrically sophisticated is this internal updating? It has been suggested that updating simply shifts the stored locations of all objects uniformly, by a common vector, when the eye or head turns. For horizontal and vertical turns, a uniform shift would often approximate the real changes in location of objects in front of the subject. But for torsional rotations, a shift would be inadequate: accurate updating would call for a more geometrically exact remapping, not shifting but rotating the stored locations through the inverse of the rotation of the eye in space. Here we asked human subjects to make eye saccades to remembered targets after torsional head rotations. Their accuracy showed that spatial updating works in the torsional dimension and operates by rotation rather than shifting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".