Microstructural abnormalities of the brain white matter in attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is an early-onset neurodevelopmental disorder with multiple behavioural problems and executive dysfunctions for which neuroimaging studies have reported a variety of abnormalities, with inconsistencies partly owing to confounding by medication and concurrent psychiatric disease. We aimed to investigate the microstructural abnormalities of white matter in unmedicated children and adolescents with pure ADHD and to explore the association between these abnormalities and behavioural symptoms and executive functions. METHODS: We assessed children and adolescents with ADHD and healthy controls using psychiatric interviews. Behavioural problems were rated using the revised Conners' Parent Rating Scale, and executive functions were measured using the Stroop Colour-Word Test and the Wisconsin Card Sorting test. We acquired diffusion tensor imaging data using a 3 T MRI system, and we compared diffusion parameters, including fractional anisotropy (FA) and mean, axial and radial diffusivities, between the 2 groups. RESULTS: Thirty-three children and adolescents with ADHD and 35 healthy controls were included in our study. In patients compared with controls, FA was increased in the left posterior cingulum bundle as a result of both increased axial diffusivity and decreased radial diffusivity. In addition, the averaged FA of the cluster in this region correlated with behavioural measures as well as executive function in patients with ADHD. LIMITATIONS: This study was limited by its cross-sectional design and small sample size. The cluster size of the significant result was small. CONCLUSION: Our findings suggest that white matter abnormalities within the limbic network could be part of the neural underpinning of behavioural problems and executive dysfunction in patients with ADHD.
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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 | 0.001 |
| 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".