Tracking Inhibitory Control in Youth With ADHD: A Multi-Modal Neuroimaging Approach
Bibliographic record
Abstract
BACKGROUND: A decreased ability to inhibit a speeded motor response is a well-studied deficit in Attention Deficit Hyperactivity Disorder (ADHD), and has been proposed as an endophenotype. Inhibitory control has been assessed reliably with the Stop Signal Task (SST) and is associated with prior documented differences in regional brain function using f-MRI. Here, we advance on these findings by examining their structural connectivity and white matter integrity with the goal of identifying a network underlying a core cognitive deficit in ADHD. METHODS: Healthy controls (N=16) and youth diagnosed with ADHD (N=60) were recruited through the Province of Ontario Neurodevelopmental Disorders Network (POND) and the Hospital for Sick Children. An f-MRI activation difference map was co-registered with each participant's white matter imaging data, representing the specific network nodes where ADHD youth diverged significantly from controls while performing the SST. Probabilistic tractography was applied from these nodes, and white matter integrity indices such as fractional anisotropy (FA) within the tracts of interest were contrasted between the groups and correlated with SST output measures, including the measure of inhibitory control, the stop signal reaction time (SSRT). RESULTS: The tracts that connected the network nodes belonged primarily to the inferior fronto-occipital fasciculus (IFOF) and cingulum. ADHD subjects showed trend differences in FA compared to controls between right inferior frontal gyrus (IFG) and right superior temporal gyrus (P= 0.09), right IFG and right posterior cingulate (P= 0.01), right anterior cingulate to posterior cingulate (p= 0.08), and between left middle temporal gyrus (BA 39) and left posterior cingulate (P=0.02). A trend correlation was found between radial diffusivity within IFG to STG white matter (IFOF) and SSRT. CONCLUSIONS: We identified potential white matter tracts related to deficient inhibitory control, elucidating the brain mechanisms of an important cognitive deficit in ADHD. These findings could be integrated into future endophenotypic biomarker studies, incorporating altogether brain structure, function, and behavior for future studies of ADHD and other psychiatric conditions that exhibit this deficit.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".