Alexithymia Correlates With the Size of the Right Anterior Cingulate
Bibliographic record
Abstract
OBJECTIVE: The authors investigated a possible relationship between interindividual variability in anterior cingulate gyrus (ACG) morphology and alexithymia. MATERIALS AND METHODS: Magnetic resonance images were obtained in 100 healthy university graduates (51 female, 49 male; mean age 25.6 y). Surface area measurements of the ACG were performed on reformatted sagittal views in both hemispheres. The Toronto Alexithymia Scale (TAS-20) and the Temperament and Character Inventory (TCI) were administered. RESULTS: Right ACG surface area significantly correlated with TAS-20 total score in men (r = 0.37; p = 0.009) and in women (r = 0.30; p = 0.034). After controlling for three TCI subscales (harm avoidance, self-directedness, and self-transcendency), the correlation between TAS-20 total and right ACG became nonsignificant in women, but was only slightly reduced (r = 0.32; p = 0.032) in men. A linear regression model with right ACG as a dependent variable revealed brain volume, TCI-harm avoidance and TAS 20 total score as significant predictors in the total sample (explained proportion of total variation (EPTV) 37%). In men, beside brain volume, only TAS-20 total score showed a highly significant contribution (EPTV 41%), whereas in women only TCI-harm avoidance was a significant predictor (EPTV 36%). CONCLUSIONS: The authors' findings indicate that there is a significant positive relation between the size of the right ACG and alexithymia as measured with the TAS in healthy subjects. This applies especially for men whereas in women ACG size is more associated with the subscale harm avoidance of the TCI. Our findings also suggest a partial lateralization of human emotion processing, especially negative emotion.
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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 | 0.001 |
| 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".