Audiovisual Multisensory Processing in Young Adults With Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
Multisensory integration is a fundamental form of sensory processing that is involved in many everyday tasks. Those with Attention-Deficit/Hyperactivity Disorder (ADHD) have characteristic alterations to various brain regions that may influence multisensory processing. The overall aim of this work was to assess how adults with ADHD process audiovisual multisensory stimuli during a complex response time task. The paradigm used was a two-alternative forced-choice discrimination task paired with continuous 64-electrode electroencephalography, allowing for the measurement of response time and accuracy to auditory, visual, and audiovisual multisensory conditions. Analysis revealed that those with ADHD ( n = 10) respond faster than neurotypical controls ( n = 12) when presented with auditory, visual, and audiovisual multisensory conditions, while also having race model violation in early response latency quantiles. Adults with ADHD also had more prominent multisensory processing over parietal-occipital brain regions at early post-stimulus latencies, indicating that altered brain structure may have important outcomes for audiovisual multisensory processing. The present study is the first to assess how those with ADHD respond to multisensory conditions during a complex response time task, and demonstrates that adults with ADHD have unique multisensory processing when assessing both behavioral response time measures and neurological measures.
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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 | 0.001 | 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".