Reduced cortical GABA and glutamate in high schizotypy
Bibliographic record
Abstract
RATIONALE: Abnormal functioning of the inhibitory gamma-aminobutyric acid (GABA) and excitatory (glutamate) systems is proposed to play a role in the development of schizophrenia spectrum disorder. Although results are mixed, previous 1H-magnetic resonance spectroscopy (MRS) studies in schizophrenia and clinical high-risk samples report these metabolites are altered in comparison to healthy controls. Currently, however, there are few studies of these metabolites in schizotypy samples, a personality dimension associated with the experience of schizophrenia and psychosis-like symptoms. OBJECTIVES: We investigated if GABA and glutamate metabolite concentrations are altered in people with high schizotypy. We also explored the relationship between resilience to stress, GABA metabolite concentrations and schizotypy. METHODS: We used MRS to examine GABA and glutamate levels in the medial prefrontal cortex in people with low and high schizotypy traits as assessed with the Schizotypal Personality Questionnaire. Resilience to stress was assessed using the Connor-Davidson Resilience Scale. RESULTS: = 0.02). Furthermore, participants with high GABA and high resilience levels were significantly more likely to be in the low schizotypy group than participants with low GABA and high resilience or high GABA and low resilience (95% CI 1.07-1.34, p < .001). CONCLUSIONS: These findings demonstrate that subclinical schizotypal traits are associated with abnormal functioning of both inhibitory and excitatory systems and suggest that these transmitters are implicated in a personality trait believed to be on a continuum with psychosis.
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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 | 0.001 | 0.001 |
| 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".