Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism
Bibliographic record
Abstract
In order to explain the cognitive and cerebral mechanisms responsible for the visuospatial peak in autism, and to document its specificity to this condition, a group of eight high-functioning individuals with autism and a visuospatial peak (HFA-P) performed a modified block-design task (BDT; subtest from Wechsler scales) at various levels of perceptual cohesiveness, as well as tasks tapping visuomotor speed, global perception, visual memory, visual search and speed of visual encoding. Their performance was compared with that of 8 autistics without a visuospatial peak (HFA-NP), 10 typically developing individuals (TD) and 8 gifted comparison participants with a visuospatial peak (TD-P). Both HFA-P and HFA-NP groups presented with diminished detrimental influence of increasing perceptual coherence compared with their BDT-matched comparison groups. Neither autistic group displayed a deficit in construction of global representations. The HFA-P group showed no differences in performance level or profile in comparison with the gifted BDT-matched [i.e. higher full-scale IQ (FSIQ)] group, apart from locally oriented perception. Diminished detrimental influence of perceptual coherence on BDT performance is both sensitive and specific to autism, and superior low-level processing interacts with locally oriented bias to produce outstanding BDT performance in a subgroup of autistic individuals. Locally oriented processing, enhanced performance in multiple tasks relying on detection of simple visual material and enhanced discrimination of first-order gratings converge towards an enhanced functioning and role of the primary visual cortex (V1) in autism. In contrast, superior or typical performance of autistics in tasks requiring global processing is inconsistent with the global-deficit-driven Weak Central Coherence hypothesis and its neurobiological magnocellular deficit counterpart.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".