Binocular depth perception in individuals at clinical high risk for psychosis: No evidence of dysfunction.
Bibliographic record
Abstract
OBJECTIVE: In the last decade the interest in the role of the visual system in schizophrenia has grown, with evidence pointing to dysfunction in bottom-up visual processing that leads to early visual processing deficits. A fundamental component of visual perception is binocular depth perception (BDP), that is, depth perception derived by the difference between the images impressed upon the left and right retina. Two studies reported impaired BDP in schizophrenia and suggested a possible developmental deficit of brain structures involved in early visual processing. The aim of this study was to examine BDP in a young population at clinical high risk (CHR) of developing psychosis to determine whether this dysfunction is present in this potentially prepsychotic period. METHODS: Forty-two CHR participants and 44 healthy controls were assessed using a computerized test of depth perception; a subsample completed a test of stereopsis. The computerized test comprised two trial blocks, with four conditions at increasing level of difficulty, in which participants were asked to discriminate the relative depth of two stimuli simultaneously presented on the screen. RESULTS: BDP was not impaired in the CHR group, whose performance was similar to that of the control group on both measures. For the CHR group performance in both tests was not correlated to positive symptoms. CONCLUSIONS: These results indicate that BDP is preserved in individuals at CHR for psychosis, and impaired BDP should not be considered a vulnerability marker for schizophrenia. Nevertheless future studies should verify BDP's potential power in predicting schizophrenia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".