Schizotypal traits are not related to multisensory integration or audiovisual speech perception
Bibliographic record
Abstract
Multisensory integration, the binding of sensory information from different sensory modalities, may contribute to perceptual symptomatology in schizophrenia, including hallucinations and aberrant speech perception. Differences in multisensory integration and temporal processing, an important component of multisensory integration, are consistently found in schizophrenia. Evidence is emerging that these differences extend across the schizophrenia spectrum, including individuals in the general population with higher schizotypal traits. In the current study, we investigated the relationship between schizotypal traits and perceptual functioning, using audiovisual speech-in-noise, McGurk, and ternary synchrony judgment tasks. We measured schizotypal traits using the Schizotypal Personality Questionnaire (SPQ), hypothesizing that higher scores on Unusual Perceptual Experiences and Odd Speech subscales would be associated with decreased multisensory integration, increased susceptibility to distracting auditory speech, and less precise temporal processing. Surprisingly, these measures were not associated with the predicted subscales, suggesting that these perceptual differences may not be present across the schizophrenia spectrum.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.008 | 0.001 |
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".