Bibliographic record
Abstract
Successful joint action often requires people to distinguish between their own and others' contributions to a shared goal. One mechanism that is thought to underlie a self-other distinction is sensory attenuation, whereby the sensory consequences of one's own actions are reduced compared to other sensory events. Previous research has shown that the auditory N1 event-related potential (ERP) response is reduced for self-generated compared to externally generated tones. The current study examined whether attenuation also occurs for jointly generated tones, which require two people to coordinate their actions to produce a single tone. ERP responses were measured when participants generated tones alone (tone onset immediately followed the participant's button press) or with a partner (tone onset immediately followed the participant's or the partner's button press, whichever occurred second). N1 attenuation was smaller for jointly generated tones compared to self-generated tones. For jointly generated tones, greater delays between the participant's and the partner's button presses were associated with reduced attenuation; moreover, only trials in which there was no delay between the participant's press and tone onset showed attenuation, whereas trials in which there were delays did not show attenuation. These findings indicate that people differentiate between their own and another person's contributions to a joint action at the sensorimotor level, even when they must act together to produce a single, shared effect.
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
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".