The controlled imitation task: a new paradigm for studying self-other control
Bibliographic record
Abstract
In the automatic imitation task (AIT) participants make a cued response during simultaneous exposure to a congruent or incongruent action made by another agent. Participants are slower to make the cued response on incongruent trials, which is thought to reflect conflict between the motor representation activated by the cue and the motor representation activated by the observed action. On incongruent trials, good performance requires the capacity to suppress the imitative action, in favor of producing the cued response. Here, we introduce a new experimental paradigm that complements the AIT, and is therefore a useful task for studying the control of self and other activated representations. In what we term the "Controlled Imitation Task (CIT)", participants are cued to make an action, but on 50% of trials, within 100 ms of this cue, an on-screen hand makes a congruent or incongruent action. If the onscreen hand moves, the participant must suppress the cued response, and instead imitate the observed action as quickly and accurately as possible. In direct contrast to the AIT, the CIT requires suppression of a self-activated motor representation, and prioritization of an imitative response. In experiment 1, we report a robust pattern of interference effects in the CIT, such that participants are slower to make the imitative response on incongruent compared to congruent trials. In experiment 2, we replicate this effect while including a non-imitative spatial-cue control condition to show that the effect is particularly robust for imitative response tendencies per se. Owing to the essentially opposite control requirements of the CIT versus the AIT (i.e., suppression of self-activated motor representations instead of suppression of other-activated motor representations), we propose that this new task is a potentially informative complementary paradigm to the AIT that can be used in studies of self-other control processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".