Differences in the Role of Context on Polar and Translational Glass Patterns
Bibliographic record
Abstract
Thresholds for stimuli that rely upon activity from early visual mechanisms can be modulated by contextual information. In the orientation domain, for example, thresholds for targets that are surrounded by parallel elements are typically higher than thresholds for targets that are surrounded by orthogonal or grey surrounds. These behavioural results are thought to reflect inhibitory interactions between neurons that are tuned to similar stimulus properties. In the current study, we evaluated whether the same contextual effects would be observed with stimuli that probe mid-level form mechanisms. Coherence thresholds were evaluated for polar (ie., concentric and radial) and translational (ie., vertical and horizontal) Glass stimuli using the method of constant stimuli and a 2IFC paradigm. Baseline coherence thresholds were first determined for stimuli with no surround (radius = 1.25°: dot density = 12%), where subjects discriminated Glass patterns from noise with no coherent form. Thresholds were then determined when stimuli were surrounded by a pattern that was either the same as, or different from, the central pattern. With translational stimuli, thresholds for all 4 subjects were higher with the same surround than they were with a different surround. With polar stimuli, thresholds for 3 subjects were lower with the same surround than they were with a different surround (for one subject, polar thresholds did not differ between the 2 surround conditions). This demonstrates that the role of the surround on translational form perception is qualitatively different from the role of the surround on polar form perception for the stimulus parameters we have chosen here. We propose that this difference can be explained in terms of differences in the extent of spatial pooling that occurs between early vs. mid-level visual neural mechanisms.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".