Auditory Pitch Perception in Autism Spectrum Disorder Is Associated With Nonverbal Abilities
Bibliographic record
Abstract
Atypical sensory perception and heterogeneous cognitive profiles are common features of autism spectrum disorder (ASD). However, previous findings on auditory sensory processing in ASD are mixed. Accordingly, auditory perception and its relation to cognitive abilities in ASD remain poorly understood. Here, children with ASD, and age- and intelligence quotient (IQ)-matched typically developing children, were tested on a low- and a higher level pitch processing task. Verbal and nonverbal cognitive abilities were measured using the Wechsler's Abbreviated Scale of Intelligence. There were no group differences in performance on either auditory task or IQ measure. However, there was significant variability in performance on the auditory tasks in both groups that was predicted by nonverbal, not verbal skills. These results suggest that auditory perception is related to nonverbal reasoning rather than verbal abilities in ASD and typically developing children. In addition, these findings provide evidence for preserved pitch processing in school-age children with ASD with average IQ, supporting the idea that there may be a subgroup of individuals with ASD that do not present perceptual or cognitive difficulties. Future directions involve examining whether similar perceptual-cognitive relationships might be observed in a broader sample of individuals with ASD, such as those with language impairment or lower IQ.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".