The Effect of Stimulus Area on Global Motion Thresholds in Children and Adults
Bibliographic record
Abstract
Performance on random-dot global motion tasks may reach adult-like levels before 4 or as late as 16 years of age, depending on the specific parameters used to create the stimuli. Later maturation has been found for slower speeds, smaller spatial displacements, and sparser dot arrays. This protracted development on global motion tasks may depend on limitations specific to spatial aspects of a motion stimulus rather than to motion mechanisms per se. The current study investigated the impact of varying stimulus area (9, 36, and 81 deg2) on the global motion coherence thresholds of children 4–6 years old and adults for three signal dot displacements (∆x = 1, 5, and 30 arcmin). We aimed to determine whether children could achieve mature performance for the smallest displacements, a condition previously found to show late maturation, when a larger stimulus area was used. Coherence thresholds were higher in children compared to adults in the 1 and 5 arcmin displacement conditions, as reported previously, and this did not change as a function of stimulus area. However, both children and adults performed better with a larger stimulus area in the 30 arcmin displacement condition only. This suggests that immature spatial integration, as measured by stimulus area, cannot account for immaturities in global motion perception.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".