Socio-Cognitive Phenotypes Differentially Modulate Large-Scale Structural Covariance Networks
Bibliographic record
Abstract
Functional neuroimaging studies have suggested the existence of 2 largely distinct social cognition networks, one for theory of mind (taking others' cognitive perspective) and another for empathy (sharing others' affective states). To address whether these networks can also be dissociated at the level of brain structure, we combined behavioral phenotyping across multiple socio-cognitive tasks with 3-Tesla MRI cortical thickness and structural covariance analysis in 270 healthy adults, recruited across 2 sites. Regional thickness mapping only provided partial support for divergent substrates, highlighting that individual differences in empathy relate to left insular-opercular thickness while no correlation between thickness and mentalizing scores was found. Conversely, structural covariance analysis showed clearly divergent network modulations by socio-cognitive and -affective phenotypes. Specifically, individual differences in theory of mind related to structural integration between temporo-parietal and dorsomedial prefrontal regions while empathy modulated the strength of dorsal anterior insula networks. Findings were robust across both recruitment sites, suggesting generalizability. At the level of structural network embedding, our study provides a double dissociation between empathy and mentalizing. Moreover, our findings suggest that structural substrates of higher-order social cognition are reflected rather in interregional networks than in the the local anatomical markup of specific regions per se.
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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) | 0.001 | 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 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".