Is there "feedback" during visual imagery? Evidence from a specificity of practice paradigm.
Bibliographic record
Abstract
The specificity of practice hypothesis predicts the development of a sensorimotor representation specific to the afferent feedback available during skill acquisition (Proteau, 1992; Proteau, Marteniuk, Girouard, & Dugas, 1987). In the present investigation, we used the specificity of practice hypothesis to test whether skill acquisition through visual imagery would lead to the development of a sensory-specific movement representation similar to one resulting from actual practice. To accomplish this objective, participants practiced walking a 12-m linear path in one of three practice conditions, full-vision (FV), no-vision (NV), or visual imagery (VI), for either 10 or 100 trials. Knowledge of spatial and/or temporal results (KR) was provided to participants following each trial during this phase. Following acquisition, participants completed 10 NV trials without KR. An analysis of root-mean-squared-error (RMSE) indicated NV participants were more accurate than both FV and VI participants in the transfer condition. We believe the equivalence in transfer RMSE between FV and VI suggests that there are similarities between the movement representations attained by FV and VI practice.
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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 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".