Perceptual and Motor Processes in Motor Imagery
Bibliographic record
Abstract
The degree to which motor imagery engages the motor system or relies on perceptual/cognitive processes is a continuing debate. Here, we used the size weight illusion to create dissociation between perception and action to address the nature of motor imagery. Participants alternated lifting bricks of equal mass but where one brick was larger than the other, resulting in a perceptual illusion. Fifty-seven participants were divided into three groups differing in the modality used for training (motor imagery, MI; and overt execution, OE) and exposure to the size weight illusion pretraining, one (MI-2) and five (MI-10 and OE) lifts of each brick. We hypothesized that the MI groups would use lifting dynamics post-training consistent with the illusion, whereas the OE group would maintain accurate lifting forces. Contrary to our hypothesis, the OE and MI-10 groups maintained the effect of the illusion post-training. In the MI-2 group, perception of the bricks' weight changed to reflect the participant's belief that large objects are heavy, and they correspondingly adjusted their lifting force post-training. These results demonstrate that perceptual and motor processes are engaged during motor imagery and that the simulation of the motor component of the movement during motor imagery guides the performed action.
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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 | 0.008 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".