Association of neuroimaging measures with facial emotional processing in healthy adults: a task fMRI study
Bibliographic record
Abstract
Investigating the neural processing of emotion-related neural circuits underlying emotional facial processing may help in understanding mental disorders. We used two subscales of the Toronto Alexithymia Scale (TAS) to assess the emotional cognitive of 25 healthy participants. A higher score indicates greater difficulty in emotional perception. In addition, participants completed a n-back task during functional magnetic resonance imaging. Psychophysiological interaction analysis was used to explore the functional connectivity (FC) of neural circuits. Next, we used elastic-net regression analysis for feature selection and conducted correlation analysis between the neuroimaging measures and questionnaire scores. Following a 3-fold cross-validation, five neuroimaging measures emerged as significant features. Results of correlation analysis demonstrated that participants with higher TAS scores exhibited increased FC between the amygdala and occipital face area during facial stimulus processing, but decreased connectivity during emotional processing. These findings suggested that individuals with poor emotional recognition exhibited increased connectivity among face-related brain regions during facial processing. However, during emotional processing, decreasing neural synchronization among neural circuits involved in emotional processing affects facial expression processing. These findings suggest potential neural marker related to subjective emotional perception, which may contribute to the diagnosis and treatment of emotional dysregulation in individuals with psychiatric conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".