Changes in Movement Control Processes Following Visuomotor Adaptation
Why this work is in the frame
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Bibliographic record
Abstract
Goal-directed reaches are modified based on previous errors experienced (i.e., offline control) and current errors experienced during movement execution (i.e., online control). It is well documented that the control processes (i.e., offline and online control) underlying well learned movements change based on the time available to complete an action, such that offline control processes are engaged to a greater extent when movements are completed in a faster movement time (MT). Here, we asked if the underlying movement control processes governing newly acquired movements also change under varying MT constraints. Sixteen participants adapted their movements to a visuomotor distortion. Following reach training trials, participants reached under Long (800-1000 ms) and Short (400-500 ms) MT constraints. Results indicate that movement errors when reaching with the rotated cursor were reduced online under the Long MT constraint compared to the Short MT constraint. Thus, the contributions of offline and online movement control processes engaged in newly acquired movements can be adjusted with changes in temporal demands.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 it