Global not local motion direction tuning of curvature encoding mechanisms
Bibliographic record
Abstract
Aim. The shape-frequency and shape-amplitude after-effects, or SFAE and SAAE, are phenomena in which adaptation to a sine-wave-shaped contour causes a shift in respectively the apparent shape-frequency and shape-amplitude of a test contour in a direction away from that of the adapting stimulus. SFAEs and SAAEs are useful for probing curvature encoding in human vision. Here we have investigated motion direction selectivity of curvature-encoding mechanisms as a function of temporal frequency. We have examined whether curvature encoding mechanisms are tuned for: (i) global motion direction, (b) local motion direction, and (c) the local motion of texture-surround inhibition. Methods. SFAEs and SAAEs were measured as a function of temporal frequency for adapting and test contours that were either the same or different in motion direction, the rationale being that if the after-effects were smaller when adaptor and test differed in their motion direction then curvature encoders must be selective for motion direction. Results. SFAEs and SAAEs (i) show selectivity to global motion direction; (ii) increase in magnitude with global temporal frequency; (iii) show no selectivity to local motion direction; (iv) show no tuning for local motion of texture-surround inhibition. Conclusion. Curvature is encoded by mechanisms that are selective to global not local motion direction.
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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".