Common structural correlates of trait impulsiveness and perceptual reasoning in adolescence
Bibliographic record
Abstract
BACKGROUND: Trait impulsiveness is a potential factor that predicts both substance use and certain psychiatric disorders. This study investigates whether there are common structural cerebral correlates of trait impulsiveness and cognitive functioning in a large sample of healthy adolescents from the IMAGEN project. METHODS: Clusters of gray matter (GM) volume associated with trait impulsiveness, Cloningers' revised temperament, and character inventory impulsiveness (TCI-R-I) were identified in a whole brain analysis using optimized voxel-based morphometry in 115 healthy 14-year-olds. The clusters were tested for correlations with performance on the nonverbal tests (Block Design, BD; Matrix Reasoning, MT) of the Wechsler Scale of Intelligence for Children IV reflecting perceptual reasoning. RESULTS: Cloningers' impulsiveness (TCI-R-I) score was significantly inversely associated with GM volume in left orbitofrontal cortex (OFC). Frontal clusters found were positively correlated with performance in perceptual reasoning tasks (Bonferroni corrected). No significant correlations between TCI-R-I and perceptual reasoning were observed. CONCLUSIONS: The neural correlate of trait impulsiveness in the OFC matches an area where brain function has previously been related to inhibitory control. Additionally, orbitofrontal GM volume was associated with scores for perceptual reasoning. The data show for the first time structural correlates of both cognitive functioning and impulsiveness in healthy adolescent subjects.
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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 | 0.000 | 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) | 0.001 | 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".