Developmental characteristics of visuomotor adaptation strategies in childhood
Bibliographic record
Abstract
Visual-motor integration is an essential skill in children’s development for acquiring new movements in dynamic environments. This requires visuomotor adaptation, in which motor commands are adjusted in response to visual feedback. Previous studies in adults suggest the contribution of two stages: an early, attentive processing stage for rapid error reduction and a later, implicit stabilization stage. However, it is unclear how these processes mature. In a child-friendly task, typically-developing children (age 6-11 years with healthy vision) moved a mouse cursor straight to a target location. During learning and relearning, visual feedback of cursor location was rotated 45°, requiring corrective movement. There were 10 baseline (no-rotation), 60 learning, 30 washout (no-rotation), and 30 relearning trials. Initial directional errors were calculated as the angular difference between lines drawn from the start to the point of peak velocity and to the target. Movement onset time and total movement time were also calculated. All measurements were compared to those of adults using the same paradigm. Younger (<8 years) and older (>8 years) children showed decreased errors across learning trials and between learning and relearning (p’s<0.05) blocks. The rate of error reduction increased with age, although children and adults reached the same level by the end of learning and relearning blocks. Errors decreased linearly across trials in younger children and exponentially in older children and adults. Onset time was slower in both groups of children than in adults. Movement time was similar across all groups during learning and relearning, and accelerated during washout in older children and adults. Younger children may achieve visuomotor adaptation in a qualitatively different manner from that of older children and adults. Early-stage processes appear to be immature before age 9, requiring reliance on slower, later-stage mechanisms. Older children use flexible, explicit movement strategies that are closer to those of adults.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".