Audiovisual temporal binding window narrows with age in autistic individuals
Bibliographic record
Abstract
Atypical sensory perception has been recognized in autistic individuals since its earliest descriptions and is now considered a key characteristic of autism. Although the integration of sensory information (multisensory integration; MSI) has been demonstrated to be altered in autism, less is known about how this perceptual process differs with age. This study aimed to assess the integration of audiovisual information across autistic children and adolescents. MSI was measured using a non-social, simultaneity judgment task. Variation in temporal sensitivity was evaluated via Gaussian curve fitting procedures, allowing us to compare the width of temporal binding windows (TBWs), where wider TBWs indicate less sensitivity to temporal alignment. We compared TBWs in age and IQ matched groups of autistic (n = 32) and neurotypical (NT; n = 73) children and adolescents. The sensory profile of all participants was also measured. Across all ages assessed (i.e., 6 through 18 years), TBWs were negatively correlated with age in the autistic group. A significant correlation was not found in the NT group. When compared as a function of child (6-12 years) and adolescent (13-18 years) age groups, a significant interaction of group (autism vs NT) by age group was found, whereby TBWs became narrower with age in the autistic, but not neurotypical group. We also found a significant main effect of age and no significant main effect of group. Results suggest that TBW differences between autistic and neurotypical groups diminishes with increasing age, indicating an atypical developmental profile of MSI in autism which ameliorates across development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".