Distinct ERP profiles for auditory processing in infants at-risk for autism and language impairment
Bibliographic record
Abstract
Early identification of autism spectrum disorder (ASD) is crucial for the formulation of effective intervention programs. Language deficits may be a hallmark feature of ASD and language delay observed in ASD shows striking similarities to that observed in children with language impairment (LI). Auditory processing deficits are seen in both LI and ASD, however, they have not previously been compared directly using Event-Related Potentials (ERPs) in the two at-risk populations. This study aims to characterize infants at-risk for ASD (HR-ASD) at the electrophysiological level and to compare them with infants at-risk for LI (HR-LI) and controls, to find specific markers with predictive value. At 12-month-old, auditory processing in HR-ASD, HR-LI and controls was characterized via ERP oddball paradigm. All infants were then evaluated at 20 months, to investigate the associations between auditory processing and language/ASD-related outcomes. In both HR-ASD and HR-LI, mismatch response latency was delayed compared to controls, whereas only HR-ASD showed overall larger P3 amplitude compared to controls. Interestingly, these ERP measures correlated with later expressive vocabulary and M-CHAT critical items in the whole sample. These results may support the use of objective measurement of auditory processing to delineate pathophysiological mechanisms in ASD, as compared to LI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".