Alexithymia and frontal–amygdala functional connectivity in North Korean refugees
Bibliographic record
Abstract
BACKGROUND: Refugees commonly experience difficulties with emotional processing, such as alexithymia, due to stressful or traumatic experiences. However, the functional connectivity of the amygdala, which is central to emotional processing, has yet to be assessed in refugees. Thus, the present study investigated the resting-state functional connectivity of the amygdala and its association with emotional processing in North Korean (NK) refugees. METHODS: This study included 45 NK refugees and 40 native South Koreans (SK). All participants were administered the Toronto Alexithymia Scale (TAS), Beck Depression Inventory (BDI), and Clinician-administered PTSD Scale (CAPS), and differences between NK refugees and native SK in terms of resting-state functional connectivity of the amygdala were assessed. Additionally, the association between the strength of amygdala connectivity and the TAS score was examined. RESULTS: Resting-state connectivity values from the left amygdala to the bilateral dorsolateral prefrontal cortex (dlPFC) and dorsal anterior cingulate cortex (dACC) were higher in NK refugees than in native SK. Additionally, the strength of connectivity between the left amygdala and right dlPFC was positively associated with TAS score after controlling for the number of traumatic experiences and BDI and CAPS scores. CONCLUSIONS: The present study found that NK refugees exhibited heightened frontal-amygdala connectivity, and that this connectivity was correlated with alexithymia. The present results suggest that increased frontal-amygdala connectivity in refugees may represent frontal down-regulation of the amygdala, which in turn may produce alexithymia.
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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) | 0.002 | 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".