Motor preparation and the effects of practice
Bibliographic record
Abstract
The purpose of the current research was to examine the effects of practice on motor preparation. Participants performed four days of practice in a simple RT paradigm. Three different unimanual movements were chosen that differed in movement amplitude and number of elements and included: short (20°), long (40°), and two-step (stop at 20°continue to 40°) movements. On day 1 and 4, a startling stimulus was used to probe the preparation process by triggering the prepared movement. We found evidence for a sequence length effect for control trials on day 1 whereby the two-step movement had an increased reaction time; however with practice this effect was minimized. During startle trials, all movements were triggered at a short latency with similar consistency to control trials. Collectively these results suggested that participants fully prepared all movements in advance, including the sequenced movement. We hypothesized that complexity may relate more to the neural commands needed to produce the movement, rather than a sequencing requirement. These results are discussed in terms of current theories for sequential movement preparation.Acknowledgments: Acknowledgements for this study go to a Natural Sciences and Engineering Research Council of Canada grant awarded to Ian M. Franks.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".