The effect of stimulus area on global motion thresholds in children and adults
Bibliographic record
Abstract
Introduction: Coherence thresholds on a global motion task vary as a function of spatial and temporal stimulus parameters. This is of particular interest when studying visual development, because these parameters can have a larger impact on the performance of young children compared to adults. For example, children perform better when presented with a denser dot array while adult performance is unaffected (Narasimhan & Giaschi, 2012). We have shown that coherence thresholds for global motion direction discrimination are immature in 4-6 year olds when smaller spatial displacement (∆x) values are used to create stimulus motion, but adult-like when larger values are used (Meier & Giaschi, 2014). The current study was designed to investigate whether the apparent immaturity in motion perception for small displacements is due to immaturity in spatial integration mechanisms. To this end, we assessed the effect of stimulus area on global motion coherence thresholds in young children. Methods: Coherence thresholds were assessed in children (4.5 – 6.5 years, M = 5.5) and adults (18.6 – 29.9 years, M = 21.3) using a two-alternative forced choice direction discrimination task with a staircase paradigm. Nine conditions were assessed: spatial displacement was 1, 5, or 30 arcmin; stimulus area was 9, 36, or 82 deg2. Participants were assessed monocularly, and conducted one staircase per condition, for a total of 9 measurements. For each participant, we calculated the change in coherence threshold as a function of stimulus area at each spatial displacement. Results: There was a significant effect of spatial displacement, such that an increase in coherence threshold with decreasing area was present for large displacements (∆x = 30 arcmin) only. There was no effect of age group, and no age group by displacement interaction. Conclusion: Immaturities in global motion perception are unlikely to be accounted for by limitations in spatial integration area. Meeting abstract presented at VSS 2017
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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) | 0.003 | 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".