Effect of Impaired Recognition and Expression of Emotions on Frontocingulate Cortices: An fMRI Study of Men With Alexithymia
Bibliographic record
Abstract
OBJECTIVE: Although the brain areas involved in emotional response and in the recognition of others' emotions have been reported, the neural bases of individual differences in affective style remain to be elucidated. Alexithymia, i.e., impairment of the ability to identify and communicate one's emotional state, influences how emotions are regulated. Alexithymia has been hypothesized to involve anterior cingulate dysfunction. Therefore, the authors searched for differential cerebral regional activation in response to emotional stimuli in subjects with alexithymia. METHOD: Two groups of eight men each were selected from 437 healthy subjects on the basis of high or low scores on the 20-item Toronto Alexithymia Scale. Using functional magnetic resonance imaging (fMRI), the authors compared the two groups for their regional cerebral activation in response to the presentation of pictures with validated positive or negative arousal capabilities. RESULTS: Men with alexithymia demonstrated less cerebral activation in the left mediofrontal-paracingulate cortex in response to highly negative stimuli and more activation in the anterior cingulate, mediofrontal cortex, and middle frontal gyrus in response to highly positive stimuli than men without alexithymia. CONCLUSIONS: These findings provide direct evidence that alexithymia, a personality trait playing a role in affect regulation, is linked with differences in anterior cingulate and mediofrontal activity during emotional stimuli processing.
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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 | 0.001 | 0.001 |
| 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".