Functional and microstructural plasticity following social and interoceptive mental training
Bibliographic record
Abstract
Abstract The human brain scaffolds social cognitive functions, including Theory of Mind, empathy and compassion, through its functional and microstructural organization. However, it remains unclear how the learning and refinement of these skills may, in turn, shape brain function and structure. Here we studied if different types of social mental training can lead to plastic changes in brain function and microstructure. We studied a group of 332 healthy adults (197 women, 20-55 years) with repeated multimodal neuroimaging and behavioral testing. Our neuroimaging approach capitalized on the quantification of cortical functional gradients and myelin-sensitive T1 relaxometry, two emerging measures of cortical functional organization and microstructure. Longitudinal analysis indicated marked changes in intrinsic cortical function and microstructure, which varied as a function of social training content. In particular, we observed consistent differential change in function and microstructure between attention-mindfulness and socio-cognitive training in regions functionally associated with attention and interoception, including insular and parietal cortices. Conversely, socio-affective and socio-cognitive training resulted in differential microstructural changes in regions classically implicated in interoceptive and emotional processing, including insular and orbitofrontal areas, but did not result in functional reorganization. Notably, longitudinal changes in cortical function and microstructure were predictive of behavioral change in attention, compassion and perspective-taking, suggesting behavioral relevance. In sum, our work provides evidence for functional and microstructural plasticity after the training of social-interoceptive functions, and provides a causal perspective on the neural basis of behavioral adaptation in human adults.
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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 | 0.000 |
| 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 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".