Atypical multisensory integration in Autism Spectrum Disorders: Cascading impacts of altered temporal processing
Bibliographic record
Abstract
A strong factor influencing multisensory integration is the temporal relationship between the sensory inputs that are combined. Individuals with Autism Spectrum Disorders (ASD) exhibit both atypical multisensory and temporal processing deficits relative to their typically developing (TD) peers. A series of behavioral and fMRI studies from our lab have focused on the link between these two processes. Using speech and non-speech stimuli with parametrically varied temporal relationships between the auditory and visual components, we showed that multisensory temporal processing is indeed altered in ASD, with the largest deficits observed with speech stimuli. The temporal changes seen with simple, non-speech stimuli are strongly correlated with behavioral measures of perceptual binding of audiovisual speech, which suggests that low-level multisensory temporal deficits have cascading effects on speech perception. To explore the neural substrates of these behavioral effects, we implemented an fMRI paradigm in individuals with ASD and TD where we presented synchronous and asynchronous speech and non-speech stimuli. We functionally localized a region in the superior temporal sulcus (pSTS), based on its involvement in multisensory binding and temporal processing and known functional and anatomical differences in ASD. Responses to audiovisual stimuli were extracted and compared across stimulus types and groups. Both TD and ASD groups show reduced pSTS activation with synchronous relative to asynchronous non-speech presentations, reflecting increased processing efficiency. For speech stimuli, only the TD group showed this effect. These data suggest differences in neural processing in pSTS may be at the core of atypical speech perception observed in ASD.
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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".