Inhibitory mechanisms in autism spectrum disorders: typical selective inhibition of location versus facilitated perceptual processing
Bibliographic record
Abstract
BACKGROUND: This study examined the inhibitory control mechanisms of selective attention in autism spectrum disorders. Two issues were engaged: First, we extend previous findings of normal inhibition of distractor identity in autism by examining whether inhibition of spatial location is also spared. The second issue concerns the selectivity of inhibition. In non-clinical participants inhibition is selectively directed to the properties of the distractor that compete for the control of action; we examined whether individuals with autism also show normal selectivity of inhibition. METHOD: A negative priming task was used to examine selective spatial inhibition in participants with autism relative to matched non-clinical controls. RESULTS: We discovered that inhibition of distractor spatial location is within normal limits in autism, as is the ability to selectively direct inhibition to task-relevant stimulus features. In addition, we unexpectedly found that the irrelevant perceptual feature of colour produced a facilitation effect in autism, which has not been observed previously in typical controls. CONCLUSIONS: Evidence of colour facilitation implicates more fluent, but presumably less adaptive, perceptual processes in autism.
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 | 0.001 |
| 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 | 0.000 |
| 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".