Aberrant anterior insula underlies interoceptive deficits in alexithymia among schizophrenia patients
Bibliographic record
Abstract
OBJECTIVE: This study aims to investigate the unique neural mechanisms underpinning abnormal interoception in schizophrenia patients with comorbid alexithymia. The focus is on identifying aberrant activation patterns and functional connectivities of the insula cortex with regions involved in emotional processing. METHODS: Fifty schizophrenia patients were assessed using the Toronto Alexithymia Scale (TAS) and the Multidimensional Assessment of Interoceptive Awareness (MAIA). Task-based fMRI scans were conducted to observe brain activation patterns during interoceptive conditions. RESULTS: Alexithymic patients showed higher alexithymia and lower interoception compared to non-alexithymic patients. During the interoceptive task, alexithymic patients exhibited reduced activation in the anterior insula (AI), while no difference was observed in the posterior insula (PI). Functional connectivity analysis revealed reduced connectivity between the AI and the anterior cingulate cortex (ACC) as well as the superior frontal gyrus (SFG) in alexithymic patients. Moreover, the connection between the AI and the ACC mediated the relationship between interoception and alexithymia. CONCLUSION: These results suggested that alexithymic schizophrenia patients struggle to integrate interoceptive afferents with emotional salience, and highlighted AI's role in the interplay between interoceptive awareness and emotional articulation in alexithymic schizophrenia, suggesting a potential neurobiological pathway for targeted interventions. TRIAL REGISTRATION: The research is registered with the China Clinical Trials Registry (CCTR), under the registration number ChiCTR2400080313 on January 15, 2024.
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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) | 0.003 | 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".