Audiovisual multisensory integration in young adults with and without attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
The present research quantified multisensory integration (MSI) in young adults with and without attention-deficit/hyperactivity disorder (ADHD). MSI is a form of sensory processing where the nervous system integrates stimuli occurring together in time and/or space (Paraskevopoulos & Herholz, 2013). Multiple brain regions involved in MSI have also been reported to be altered in individuals with ADHD (Proal et al., 2011), which poses the question whether those with ADHD experience altered MSI. Participants completed a two-alternative forced-choice discrimination task while whole-head 64-electrode electroencephalography (EEG) was recorded (10 ADHD; 12 Neurotypicals). Stimulus presentation conditions were auditory-alone (~300 ms duration; verbalization adjusted to comfortable volume per participant), visual-alone (250 ms duration; red, blue, or green-filled circle on black background), or a semantically congruent audiovisual. stimulus. The Principle of Superposition of Electrical Fields was used to assess MSI via EEG (Brandwein et al., 2011). The ADHD group demonstrated significantly shorter response times to each stimulus type (P = 0.048) and both groups responded most accurately to the auditory-alone stimulus compared to the visual-alone stimulus (P < 0.001). EEG analysis showed MSI occurring in both groups (P = 0.046) from 110-130 ms post stimulus over parietal occipital brain regions. However, the ADHD group showed greater MSI at this latency and brain region (P = 0.033). This is the first work to suggest that young adults with ADHD process audiovisual multisensory information differently during a complex RT task than neurotypical controls, and this may be related to the various altered neurological structures shown in previous research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".