Visual working memory and sensory processing in autistic children
Bibliographic record
Abstract
While atypical sensory processing is one of the more ubiquitous symptoms in autism spectrum disorder, the exact nature of these sensory issues remains unclear, with different studies showing either enhanced or deficient sensory processing. Using a well-established continuous cued-recall task that assesses visual working memory, the current study provides novel evidence reconciling these apparently discrepant findings. Autistic children exhibited perceptual advantages in both likelihood of recall and recall precision relative to their typically-developed peers. When autistic children did make errors, however, they showed a higher probability of erroneously binding a given colour with the incorrect spatial location. These data align with neural-architecture models for feature binding in visual working memory, suggesting that atypical population-level neural noise in the report dimension (colour) and cue dimension (spatial location) may drive both the increase in probability of recall and precision of colour recall as well as the increase in proportion of binding errors when making an error, respectively. These changes are likely to impact core symptomatology associated with autism, as perceptual binding and working memory play significant roles in higher-order tasks, such as communication.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".