Trait compassion is associated with the neural substrate of empathy
Bibliographic record
Abstract
Individual differences in the personality trait Agreeableness underlie humans' ability to interpret social cues and coordinate effectively with others. However, previous investigations of the neural basis of Agreeableness have yielded largely inconsistent results. Recent evidence has demonstrated that Agreeableness can be divided into two, correlated subdimensions. Compassion reflects tendencies toward empathy, sympathy, and concern for others, while Politeness reflects tendencies toward compliance and refraining from aggression and exploitation. The present study seeks to clarify the neural substrates of Agreeableness by examining whether structural differences in the brain show distinct associations with Compassion and Politeness. Results of a meta-analysis of fMRI studies examining empathy were used to generate hypotheses about the brain regions and networks that underlie trait Compassion. Results of a large-scale structural neuroimaging investigation (N = 275) were largely consistent with the meta-analysis: Compassion was positively correlated with gray matter volume in the bilateral anterior cingulate cortex (ACC) and anterior insula (AI). Further, these differences appear to be associated with Compassion specifically, as opposed to Politeness, suggesting that these two traits have at least partially distinct neuroanatomical substrates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".