Deficits in auditory predictive coding in individuals with the psychosis risk syndrome: Prediction of conversion to psychosis.
Bibliographic record
Abstract
The mismatch negativity (MMN) event-related potential (ERP) component is increasingly viewed as a prediction error signal elicited when a deviant sound violates the prediction that a frequent "standard" sound will repeat. Support for this predictive coding framework emerged with the identification of the repetition positivity (RP), a standard stimulus ERP component that increases with standard repetition and is thought to reflect strengthening of the standard's memory trace and associated predictive code. Using electroencephalographic recordings, we examined the RP elicited by repeating standard tones presented during a traditional "constant standard" MMN paradigm in individuals with the psychosis risk syndrome (PRS; n = 579) and healthy controls (HC; n = 241). Clinical follow-up assessments identified PRS participants who converted to a psychotic disorder (n = 77) and PRS nonconverters who were followed for the entire 24-month clinical follow-up period and either remained symptomatic (n = 144) or remitted from the PRS (n = 94). In HC, RP linearly increased from early- to late-appearing standards within local trains of repeating standards (p < .0001), consistent with auditory predictive code/memory trace strengthening. Relative to HC, PRS participants showed a reduced RP across standards (p = .0056). PRS converters showed a relatively small RP deficit for early appearing standards relative to HC (p = .0.0107) and a more prominent deficit for late-appearing standards (p = .0006) relative to both HC and PRS-remitted groups. Moreover, greater RP deficits predicted shorter time to conversion in a subsample of unmedicated PRS individuals (p = .02). Thus, auditory predictive coding/memory trace deficits precede psychosis onset and predict future psychosis risk in PRS individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".