Motion aftereffect in depth based on binocular information
Bibliographic record
Abstract
We examined whether a negative motion aftereffect occurs in the depth direction following adaptation to motion in depth based on changing disparity and/or interocular velocity differences. To dissociate these cues, we used three types of adapters: random-element stereograms that were correlated (1) temporally and binocularly, (2) temporally but not binocularly, and (3) binocularly but not temporally. Only the temporally correlated adapters contained coherent interocular velocity differences while only the binocularly correlated adapters contained coherent changing disparity. A motion aftereffect in depth occurred after adaptation to the temporally correlated stereograms while little or no aftereffect occurred following adaptation to the temporally uncorrelated stereograms. Interestingly, a monocular test pattern also showed a comparable motion aftereffect in a diagonal direction in depth after adaptation to the temporally correlated stereograms. The lack of the aftereffect following adaptation to pure changing disparity was also confirmed using spatially separated random-dot patterns. These results are consistent with the existence of a mechanism sensitive to interocular velocity differences, which is adaptable (at least in part) at binocular stages of motion-in-depth processing. We did not find any evidence for the existence of an "adaptable" mechanism specialized to see motion in depth based on changing disparity.
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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 | 0.001 | 0.000 |
| 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".