Finding normal-to-better neurocognitive indexes in individuals with schizotypal traits using a social role task
Bibliographic record
Abstract
Schizophrenia patients make more errors and have longer reaction times (RTs) than healthy controls in most cognitive tasks. Deficits are also observed in subclinical participants having high scores on the schizotypal personality questionnaire (SPQ). They are accompanied by smaller amplitudes of the event-related brain potentials (ERPs) that index attention and semantic- and working-memory. These functions are thus thought to be impaired in individuals having various schizophrenia attributes (SzAs). Nevertheless, normal RTs were recently found in SzAs during a particular self-referential task where half of the stimuli were names of extraordinary social roles (e.g., genius). Each name (ordinary or extraordinary) was presented individually, and participants were asked to decide whether or not they would consider themselves performing the role at any moment of their lives. To further test an absence of cognitive deficits in this task, the ERPs elicited by names of social roles were also examined in 175 healthy participants. The absence of longer RTs in high- than in low-SPQs was replicated. Moreover, the ERPs of high SPQs had larger occipital N1s, larger P2s and larger occipital N400s than those of low SPQs while late positive potentials (LPPs) were of similar amplitudes. Such results are consistent with clinical observations of greater attention and faster processing of stimuli related to extraordinary/delusional beliefs. Further studies should test whether the cognitive deficits found in SzAs are due to the use of tasks and stimuli that are less within their focus of interest than within that of healthy controls.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".