ADHD desynchronizes brain activity during watching a distracted multi-talker conversation
Bibliographic record
Abstract
Individuals with attention-deficit/hyperactivity disorder (ADHD) have difficulties navigating dynamic everyday situations that contain multiple sensory inputs that need to either be attended to or ignored. As conventional experimental tasks lack this type of everyday complexity, we administered a film-based multi-talker condition with auditory distractors in the background. ADHD-related aberrant brain responses to this naturalistic stimulus were identified using intersubject correlations (ISCs) in functional magnetic resonance imaging (fMRI) data collected from 51 adults with ADHD and 29 healthy controls. A novel permutation-based approach introducing studentized statistics and subject-wise voxel-level null-distributions revealed that several areas in cerebral attention networks and sensory cortices were desynchronized in participants with ADHD (n = 20) relative to healthy controls (n = 20). Specifically, desynchronization of the posterior parietal cortex occurred when irrelevant speech or music was presented in the background, but not when irrelevant white noise was presented, or when there were no distractors. We also show regionally distinct ISC signatures for inattention and impulsivity. Finally, post-scan recall of the film contents was associated with stronger ISCs in the default-mode network for the ADHD and in the dorsal attention network for healthy controls. The present study shows that ISCs can further our understanding of how a complex environment influences brain states in ADHD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".