Atypical rapid audio‐visual temporal recalibration in autism spectrum disorders
Bibliographic record
Abstract
Changes in sensory and multisensory function are increasingly recognized as a common phenotypic characteristic of Autism Spectrum Disorders (ASD). Furthermore, much recent evidence suggests that sensory disturbances likely play an important role in contributing to social communication weaknesses-one of the core diagnostic features of ASD. An established sensory disturbance observed in ASD is reduced audiovisual temporal acuity. In the current study, we substantially extend these explorations of multisensory temporal function within the framework that an inability to rapidly recalibrate to changes in audiovisual temporal relations may play an important and under-recognized role in ASD. In the paradigm, we present ASD and typically developing (TD) children and adolescents with asynchronous audiovisual stimuli of varying levels of complexity and ask them to perform a simultaneity judgment (SJ). In the critical analysis, we test audiovisual temporal processing on trial t as a condition of trial t - 1. The results demonstrate that individuals with ASD fail to rapidly recalibrate to audiovisual asynchronies in an equivalent manner to their TD counterparts for simple and non-linguistic stimuli (i.e., flashes and beeps, hand-held tools), but exhibit comparable rapid recalibration for speech stimuli. These results are discussed in terms of prior work showing a speech-specific deficit in audiovisual temporal function in ASD, and in light of current theories of autism focusing on sensory noise and stability of perceptual representations. Autism Res 2017, 10: 121-129. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".