Brain and Behavioural Correlates of Social Functioning Components: Empathy, Compassion, and Theory of Mind
Bibliographic record
Abstract
Social functioning (SF)—the capacity to understand, care for, and act with others—rests on empathy, compassion, and Theory of Mind (ToM). Yet their measurement, neural substrates, and ties to mental health are poorly understood. Drawing on large cross-sectional samples, validated questionnaires, and structural as well as functional neuroimaging, this dissertation examines psychometric, psychological, demographic, and neurobiological aspects of the three SF components.<br/><br/>A psychometric analysis shows that negatively worded items weaken the psychometric properties of the Toronto Empathy Questionnaire in Slavic languages; rewriting them markedly improves reliability and validity. Neuroimaging results reveal that sulcal depth predicts trait emotional empathy more accurately than cortical thickness. Systematic reviews identify the insula and reward circuitry (e.g., caudate nucleus) as key components for trait compassion, while reduced right superior temporal pole activity characterises diminished compassionate states. In ADHD, ToM deficits co-occur with atypical activation across frontal, temporal, parietal, and occipital regions.<br/><br/>Network analyses link total trait empathy positively to anxiety and depression, yet item-level patterns reveal a more complicated relationship: resonating with others’ joy is indirectly linked with lower anxiety through improved relationship satisfaction. Altogether, the findings highlight that SF emerges from dynamic interactions among neural circuits, personality traits, environmental contexts, and cultural norms, and that item-level, culturally sensitive measurement is important. <br/><br/>The thesis proposes that further advancements in the SF research can be reached by building strong theories that would refine prediction and guide personalised interventions targeting empathy, compassion, and ToM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".