Sensitivity to Biological and Global Motion: Similar in their Protracted Development but Different in Susceptibility to Visual Deprivation
Bibliographic record
Abstract
We used a staircase procedure to test sensitivity to biological and global motion in normally developing children aged 6-9, 9-12, and 12-15 years, and adults (n = 20 per group), as well as in eight patients treated for bilateral congenital cataracts (11-30 years old). In the biological motion task, participants discriminated biological motion from scrambled displays, with the number of added noise dots varied across trials. Thresholds were defined as the maximum number of noise dots tolerated for accurate discrimination. In the global motion tasks, participants discriminated upward from downward motion in random-dot kinematograms moving at 4 and 18 deg/sec in separate blocks. Thresholds were defined as the minimum percentage of signal dots required to accurately determine the overall direction of motion. Results revealed a similar, long developmental trajectory for sensitivity to biological and global motion (ps<0.0001). Only the 12- to 15-year'olds showed adult-like performance, suggesting that the extrastriate mechanisms that integrate local motion cues over time and space take many years to mature. Although global motion thresholds were lower for faster than slower speeds at every age (ps<0.0001), developmental trends did not differ across the two speeds (p>0.10). In contrast, early bilateral deprivation had different effects on the two types of motion perception. Z-scores based on age-appropriate norms indicated a large deficit in processing both speeds of global motion (mean Z-score = -4.21 and -5.85 for fast and slow speeds, ps<0.01) but no abnormality for processing biological motion (mean Z-score = -0.19, p>0.70). The adverse effect of visual deprivation was equivalent at the two speeds of global motion (p>0.20) and greater than the (non-significant) effect on biological motion (ps<0.01). The spared sensitivity to biological motion might be explained by a neural network that is stimulated by body movements during the period of visual deprivation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".