Emotional contagion for pain is intact in autism spectrum disorders
Bibliographic record
Abstract
Perceiving others in pain generally leads to empathic concern, consisting of both emotional and cognitive processes. Empathy deficits have been considered as an element contributing to social difficulties in individuals with autism spectrum disorders (ASD). Here, we used functional magnetic resonance imaging and short video clips of facial expressions of people experiencing pain to examine the neural substrates underlying the spontaneous empathic response to pain in autism. Thirty-eight adolescents and adults of normal intelligence diagnosed with ASD and 35 matched controls participated in the study. In contrast to general assumptions, we found no significant differences in brain activation between ASD individuals and controls during the perception of pain experienced by others. Both groups showed similar levels of activation in areas associated with pain sharing, evidencing the presence of emotional empathy and emotional contagion in participants with autism as well as in controls. Differences between groups could be observed at a more liberal statistical threshold, and revealed increased activations in areas involved in cognitive reappraisal in ASD participants compared with controls. Scores of emotional empathy were positively correlated with brain activation in areas involved in embodiment of pain in ASD group only. Our findings show that simulation mechanisms involved in emotional empathy are preserved in high-functioning individuals with autism, and suggest that increased reappraisal may have a role in their apparent lack of caring behavior.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".