Spatial coding for memory-guided reaching in visual and pictorial spaces
Bibliographic record
Abstract
An essential difference between pictorial space displayed as paintings, photographs, or computer screens, and the visual space experienced in the real world is that the observer has a defined location, and thus valid information about distance and direction of objects, in the latter but not in the former. Thus egocentric information should be more reliable in visual space, whereas allocentric information should be more reliable in pictorial space. The majority of studies relied on pictorial representations (images on a computer screen), leaving it unclear whether the same coding mechanisms apply in visual space. Using a memory-guided reaching task in virtual reality, we investigated allocentric coding in both visual space (on a table in virtual reality) and pictorial space (on a monitor that is on the table in virtual reality). Our results suggest that the brain uses allocentric information to represent objects in both pictorial and visual space. Contrary to our hypothesis, the influence of allocentric cues was stronger in visual space than in pictorial space, also after controlling for retinal stimulus size, confounding allocentric cues, and differences in presentation depth. We discuss possible reasons for stronger allocentric coding in visual than in pictorial space.
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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 | 0.000 |
| 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".