Is the motor contagion effect an artifact of eye movements?
Bibliographic record
Abstract
The 'motor contagion' effect manifests when a participant performs one action while simultaneously observing an action performed by another person; observing an incongruent action relative to a congruent action results in an increase in spatial displacement along the orthogonal plane to the participant's intended movement. Motor contagion is often cited as an example of motor interference produced by the activation of motor neurons associated with the observed action that compete with the target action. In the typical motor contagion paradigm, little attention has been given to the complexities of how an individual's eye movement may influence action execution. Indeed, experimenters often instruct their participants to follow the hand of the actor with their eyes while completing the task. It is well known that hands follow eyes; therefore, this instruction could have a large impact on the way motor 'contagion' manifests. Thus, we investigated if concurrently executed eye movements could explain the motor contagion effect. Participants made horizontal arm movements while observing an actor making either vertical (incongruent) or horizontal (congruent) movements under three conditions: no instruction, instruction to maintain fixation on a central cross, or instruction to follow the actor's hand with their eyes. The eye and hand movements of the participants were recorded. Movement variability in the secondary axis was larger in the incongruent than congruent movement conditions only in the 'follow' condition. These data indicate that motor contagion-like effects may be an artifact of simultaneously executed eye movements. We conclude that, at least in this case, an actor's actions are not 'contagious' unless the participant has an existing propensity to follow an actor's actions with their eyes. Meeting abstract presented at VSS 2016
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".