Inter-subject gamma oscillation synchronization as a biomarker of abnormal processing of social interaction in ADHD
Bibliographic record
Abstract
Children with attention-deficit hyperactivity disorder (ADHD) have difficulties in social interactions. Studying brain activity during social interactions is difficult with conventional artificial stimuli. This pioneering study examined the neural correlates of social perception in children with ADHD and matched controls using naturalistic stimuli. We presented 20 children with ADHD and 20 age-and-sex-matched controls with tailored movies featuring high- or low-level social interactions while recording electroencephalographic signals. Both groups exhibited synchronized gamma-band oscillations, but controls demonstrated greater inter-subject correlations. Additionally, the difference in inter-subject correlations between high- and low-interaction movies was significantly larger in controls compared to ADHD patients. Between 55 and 75 Hz comparing viewing high interaction movies with low interaction moves, controls had a significantly larger weighting in the right parietal lobe, while ADHD patients had a significantly smaller weighting in the left occipital lobe. These findings reveal distinct spatiotemporal neural signatures in social interaction processing among children with ADHD and controls using naturalistic stimuli. These neural markers offer potential for group differentiation and assessing intervention efficacy, advancing our understanding ADHD-related social interaction mechanisms.
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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".