<scp>N400</scp> event‐related brain potential and functional outcome in persons at clinical high risk for psychosis: A longitudinal study
Bibliographic record
Abstract
BACKGROUND: The N400 event-related brain potential (ERP) semantic priming effect is thought to reflect activation by meaningful stimuli of related concepts in semantic memory and has been found to be deficient in schizophrenia. We tested the hypothesis that, among individuals at clinical high risk (CHR) for psychosis, N400 semantic priming deficits predict worse symptomatic and functional outcomes after one year. METHODS: We measured N400 semantic priming at baseline in CHR patients (n = 47) and healthy control participants (n = 25) who viewed prime words each followed by a related or unrelated target word, at stimulus-onset asynchronies (SOAs) of 300 or 750 ms. We measured patients' psychosis-like symptoms with the Scale of Prodromal Symptoms (SOPS) Positive subscale, and academic/occupational and social functioning with the Global Functioning (GF):Role and Social scales, respectively, at baseline and one-year follow-up (n = 29). RESULTS: CHR patients exhibited less N400 semantic priming than controls across SOAs; planned contrasts indicated this difference was significant at the 750-ms but not the 300-ms SOA. In patients, reduced N400 semantic priming at the 750-ms SOA was associated with lower GF:Social scores at follow-up, and greater GF:Social decrements from baseline to follow-up. Patients' N400 semantic priming was not associated with SOPS Positive or GF:Role scores at follow-up, or change in these from baseline to follow-up. CONCLUSIONS: In CHR patients, reduced N400 semantic priming at baseline predicted worse social functioning after one year, and greater decline in social functioning over this period. Thus, the N400 may be a useful prognostic biomarker of real-world functional outcome in CHR patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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, 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".