Healthy co-twins of patients with affective disorders show reduced risk-related activation of the insula during a monetary gambling task
Bibliographic record
Abstract
BACKGROUND: Healthy first-degree relatives of patients with affective disorders are at increased risk for affective disorders and express discrete structural and functional abnormalities in the brain reward system. However, value-based decision making is not well understood in these at-risk individuals. METHODS: We investigated healthy monozygotic and dizygotic twins with or without a co-twin history of affective disorders (high-risk and low-risk groups, respectively) using functional MRI during a gambling task. We assessed group differences in activity related to gambling risk over the entire brain. RESULTS: We included 30 monozygotic and 37 dizygotic twins in our analysis. Neural activity in the anterior insula and ventral striatum increased linearly with the amount of gambling risk in the entire cohort. Individual neuroticism scores were positively correlated with the neural response in the ventral striatum to increasing gambling risk and negatively correlated with individual risk-taking behaviour. Compared with low-risk twins, the high-risk twins showed a bilateral reduction of risk-related activity in the middle insula extending into the temporal cortex with increasing gambling risk. Post hoc analyses revealed that this effect was strongest in dizygotic twins. LIMITATIONS: The relatively old average age of the mono- and dizygotic twin cohort (49.2 yr) may indicate an increased resilience to affective disorders. The size of the monozygotic high-risk group was relatively small (n = 13). CONCLUSION: The reduced processing of risk magnitude in the middle insula may indicate a deficient integration of exteroceptive information related to risk-related cues with interoceptive states in individuals at familial risk for affective disorders. Impaired risk processing might contribute to increased vulnerability to affective disorders.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".