Neuroimaging in Attention-Deficit Hyperactivity Disorder: Beyond the Frontostriatal Circuitry
Bibliographic record
Abstract
OBJECTIVES: To review the findings of structural and functional neuroimaging studies in attention-deficit hyperactivity disorder (ADHD), with a focus on abnormalities reported in brain regions that lie outside the frontostriatal circuitry, which is currently believed to play a central role in the pathophysiology of ADHD. METHODS: Relevant publications were found primarily by searching the MEDLINE and PubMed databases using the keywords ADHD and the abbreviations of magnetic resonance imaging (MRI), functional MRI, positron emission tomography, and single photon emission computed tomography. The reference lists of the articles found through the databases were then reviewed for the purpose of finding additional articles. RESULTS: There is now substantial evidence of structural and functional alterations in regions outside the frontostriatal circuitry in ADHD, most notably in the cerebellum and the parietal lobes. CONCLUSIONS: Although there is compelling evidence suggesting that frontostriatal dysfunction may be central to the pathophysiology of ADHD, the neuroimaging findings point to distributed neural substrates rather than a single one. More research is needed to elucidate the nature of contributions of nonfrontostriatal regions to the pathophysiology of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".