Personality and Neural Correlates of Mentalizing Ability
Bibliographic record
Abstract
Theory of mind, or mentalizing, defined as the ability to reason about another's mental states, is a crucial psychological function that is disrupted in some forms of psychopathology, but little is known about how individual differences in this ability relate to personality or brain function. One previous study linked mentalizing ability to individual differences in the personality trait Agreeableness. Agreeableness encompasses two major subdimensions: Compassion reflects tendencies toward empathy, prosocial behaviour, and interpersonal concern, whereas Politeness captures tendencies to suppress aggressive and exploitative impulses. We hypothesized that Compassion but not Politeness would be associated with better mentalizing ability. This hypothesis was confirmed in Study 1 ( N = 329) using a theory of mind task that required reasoning about the beliefs of fictional characters. Post hoc analyses indicated that the honesty facet of Agreeableness was negatively associated with mentalizing. In Study 2 ( N = 217), we examined whether individual differences in mentalizing and related traits were associated with patterns of resting–state functional connectivity in the brain. Performance on the theory of mind task was significantly associated with patterns of connectivity between the dorsal medial and core subsystems of the default network, consistent with evidence implicating these regions in mentalization. Copyright © 2017 European Association of Personality Psychology
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".