Greater involvement of action simulation mechanisms in emotional vs cognitive empathy
Bibliographic record
Abstract
Empathy is crucial for successful interpersonal interactions, and it is impaired in many psychiatric and neurological disorders. Action-perception matching, or action simulation mechanisms, has been suggested to facilitate empathy by supporting the simulation of perceived experience in others. However, this remains unclear, and the involvement of the action simulation circuit in cognitive empathy (the ability to adopt another's perspective) vs emotional empathy (the capacity to share and react affectively to another's emotional experience) has not been quantitatively compared. Presently, healthy adults completed a classic cognitive empathy task (false belief), an emotional empathy task and an action simulation button-pressing task during functional magnetic resonance imaging. Conjunction analyses revealed common recruitment of the inferior frontal gyrus (IFG), thought to be critical for action-perception matching, during both action simulation and emotional, but not cognitive, empathy. Furthermore, activation was significantly greater in action simulation regions in the left IFG during emotional vs cognitive empathy, and activity in this region was positively correlated with mean feeling ratings during the emotional empathy task. These findings provide evidence for greater involvement of action simulation mechanisms in emotional than cognitive empathy. Thus, the action simulation circuit may be an important target for delineating the pathophysiology of disorders featuring emotional empathy impairments.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".