Development of Multiple Movement Representations With Practice: Specificity Versus Flexibility
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The question addressed in the present experiment was whether an individual who practices a task under different conditions of afferent information develops different movement representations, each of which is based on the most accurate source of afferent information for movement control. In Experiment 1, participants (N = 23) performed a manual aiming movement in a target-only condition for 520 trials before performing in a normal vision condition for an equivalent amount of practice. Control groups performed all practice trials in either a normal vision or a target-only condition. The results revealed that the movement representation developed in the initial (target-only) practice phase remained accessible for movement planning and control. The results of Experiment 2 indicated, however, that participants did not maintain such a representation when their initial practice in the target-only condition was reduced (40 or 160 trials) before they had extensive practice in normal vision. Those results indicate that extensive practice in a target-only and then in a normal vision condition enables an individual to plan and control his or her movement on the basis of the most efficient source of available afferent information. Because visual afferent information provides optimal information for ensuring movement accuracy, however, if initial practice in the target-only condition is only modest or moderate it is likely that that information source will progressively dominate all other sources of afferent information for movement planning and control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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