Audiovisual Multisensory Integration and Evoked Potentials in Young Adults With and Without Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
The purpose of this study was to assess how young adults with Attention-Deficit/Hyperactivity Disorder process audiovisual multisensory stimuli using behavioural and neurological measures. Adults with a clinical diagnosis of ADHD (n=10) and neurotypical controls (n=11) completed a simple response time task, consisting of auditory, visual, and audiovisual multisensory conditions. Continuous 64-electrode electroencephalography (EEG) was collected to assess neurological responses to each condition. The audiovisual multisensory condition resulted in the shortest response times for both populations. Analysis using the race model (Miller, 1982) demonstrated that those with ADHD had violation of the race model earlier in the response, which may be a marker for impulsivity. EEG analysis revealed that both groups had early multisensory integration occur following multisensory stimulus onset. There were also significant group differences in event-related potentials (ERPs) in frontal, parietal, and occipital brain regions, which are regions reported to be altered in those with ADHD. This study presents results examining multisensory processing in the population of adults with ADHD, and can be used as a foundation for future ADHD research using developmental research designs as well as the development of novel technological supports.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".