Theta Oscillations Assessed From a Passive Auditory Oddball Paradigm in Individuals at Clinical High-Risk for Psychosis and Healthy Control Individuals: Associations with Clinical Outcomes and Mismatch Negativity
Bibliographic record
Abstract
Background: Reduced mismatch negativity (MMN) is a widely replicated schizophrenia biomarker. Time-frequency analyses suggest that deficient phase synchrony and/or power of electroencephalography (EEG) event-related oscillations, especially theta, contribute to MMN deficits in schizophrenia. Whether theta oscillations assessed from a passive auditory oddball paradigm are abnormal in clinical high-risk for psychosis (CHR-P) individuals and whether these oscillations predict CHR-P clinical outcomes remain unclear. These questions were addressed using data from NAPLS2 (North American Prodrome Longitudinal Study 2). Methods: EEG was recorded from 77 CHR-P individuals who converted to psychosis (CHR-Cs), 238 CHR-P nonconverters (CHR-NCs) who completed a 24-month follow-up, and 241 healthy control (HC) individuals. Theta oscillations elicited by standard and deviant tones were calculated. Theta (4-6 Hz) intertrial phase coherence (ITC) and total power were compared between groups and evaluated as predictors of time to psychosis conversion in the full CHR-P sample. Furthermore, analyses of covariance were used to assess whether theta deficits persisted while covarying for MMN. Results: s < .039). Conclusions: These results implicate abnormalities in microcircuit generators of theta oscillations in CHR-P individuals at highest risk.
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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 | 0.000 |
| 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".