Orienting of visual attention among persons with autism spectrum disorders: reading versus responding to symbolic cues
Bibliographic record
Abstract
BACKGROUND: Are persons with autism spectrum disorders (ASD) slower than typically developing individuals to read the meaning of a symbolic cue in a visual orienting paradigm? METHODS: Participants with ASD (n = 18) and performance mental age (PMA) matched typically developing children (n = 16) completed two endogenous orienting conditions in which the cue exposure time and response preparation time were manipulated within a consistent series of cue-target stimulus onset asynchronies (SOAs). RESULTS: Participants with ASD displayed facilitation effects at all SOAs, whereas typically developing children displayed facilitation effects only at shorter SOAs. The magnitude of the facilitation effect was greater for the group with ASD at 400ms SOA. Both groups showed similar effects of condition, with similar patterns of facilitation in both conditions. CONCLUSION: Persons with ASD were not slower to read the symbolic cue, as the effect was elicited by brief cues within longer SOAs before target onset. The participants with ASD were also less efficient in using the predictability of the cues to guide responding. The difficulties of participants with ASD on endogenous orienting occur at the response selection level, not the perceptual level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".