N400 event‐related brain potential index of semantic processing and two‐year clinical outcomes in persons at high risk for psychosis: A longitudinal study
Bibliographic record
Abstract
The N400 event-related brain potential (ERP) semantic priming effect reflects greater activation of contextually related versus unrelated concepts in long-term semantic memory. Deficits in this measure have been found in persons with schizophrenia and those at clinical high risk (CHR) for this disorder. In CHR patients, we previously found that these deficits predict poorer social functional outcomes after 1 year. In the present study, we tested whether these deficits predicted greater psychosis-spectrum symptom severity and functional impairment over 2 years. We measured N400 semantic priming effects at baseline in CHR patients (n = 47) who viewed prime words each followed by a related/unrelated target word at stimulus-onset asynchronies (SOAs) of 300 or 750 ms. We measured psychosis-spectrum symptoms using the Structured Interview for Prodromal Symptoms and role and social functioning with the Global Functioning: Role and Social scales, at baseline, 1 (n = 29) and 2 years (n = 25). There was a significant interaction between the N400 semantic priming effect at the 300-ms SOA and time on GF:Role scores, indicating that, contrary to expectations, smaller baseline N400 semantic priming effects were associated with more improvement in role functioning from baseline to Year 1, but baseline N400 priming effects did not predict role functioning at Year 2. N400 priming effects were not significantly associated with different trajectories in psychosis-spectrum symptoms or social functioning. Thus, CHR patients' N400 semantic priming effects did not predict clinical outcomes over 2 years, suggesting that this ERP measure may have greater value as a state or short-term prognostic neurophysiological biomarker.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".