The assumed motor capabilities of a partner influence motor imagery in a joint serial disc transfer task
Bibliographic record
Abstract
Motor imagery (MI) of one's own movements is thought to involve the sub-threshold activation of one's own motor codes. Movement coordination during joint action is thought to occur because co-actors integrate a simulation of their own actions with the simulated actions of the partner. The present experiments gained insight into MI of joint action by investigating if and how the assumed motor capabilitiesof the imaginary partner affected MI. Participants performed a serial disc transfer task alone and then imagined performing the same task alone and with an imagined partner. In the individual tasks, participants transferred all four discs. In the joint task, participants imagined themselves transferring the first 2 discs and a partner transferring the last 2 discs. The description of the imagined partner (high/low performer) was manipulated across blocks to determine if participants adapted their MI of the joint task based on the partner's characteristics. Results revealed that imagined movement times (MTs) were shorter when the description of the imagined partner was a 'high' performer compared to a 'low' performer. Interestingly, participants not only adjusted the partner's portion of the task, but they also adjusted their own portion of the task - imagined MTs of the first disc transfers were shorter when imagining performing the task with a high performer than with a low performer. These findings suggest that MI is based on the simulation of one's own response code, and that the adaptation of MI to their partner's movements influences the MI of one's own movements.
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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) | 0.001 | 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".