"Imagine That!": Transfer of execution effects on accuracy of imagined aiming movements
Bibliographic record
Abstract
Ideomotor theory states that the codes that represent action and the perceptual consequences of those actions are tightly bound in a common code. For action imagination, bound action and perceptual codes are thought to be internally activated at a sub-threshold level through an action simulation process. In support of this hypothesis, previous research revealed that imagined movement times (MTs) for reciprocal aiming movements were closer to actual execution MTs after the participants gained experience executing the task and that this effect is task specific. These results were suggested to occur because the binding and enhancing of common codes occurs through experience with a specific action and its perceptual consequences. The current study was conducted to investigate whether the effects of action execution on the accuracy of imagined MTs can be transferred to reciprocal aiming movements that are not actually executed but whose level of difficulty lies within those executed. In other words, we sought to determine if improvements in accuracy of action imagination occur only with experience of specific combinations of target width and amplitude or with experience completing the task in general. To this end, participants were asked to imagine themselves performing reciprocal aiming movements with indexes of difficulty (IDs) ranging from 2 to 4 both before and after executing aiming movements with IDs of only 2 and 4. Changes in accuracy of imagined movements were assessed by analyzing the change in imagined movement time from before to after execution. Consistent with previous findings, there was an overall reduction in imagined MTs following task execution. Critically, there was also a reduction in imagined MTs across the IDs that were not executed. These results suggest that individuals are able to accurately interpolate MTs in action imagination following experience with aiming movements whose IDs lie on the outside of the range. Acknowledgments: This research was supported by the Natural Sciences and Engineering Research Council and the Ontario Ministry for Research and Innovation.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".