Increased cortical inhibition in persons with schizophrenia treated with clozapine
Bibliographic record
Abstract
It has been previously demonstrated that unmedicated persons with schizophrenia have deficits in cortical inhibition (CI) as indexed with transcranial magnetic stimulation (TMS). This inhibition is largely mediated by cortical GABAergic mechanisms. It has also been demonstrated that these inhibitory deficits may be normalized with the use of atypical antipsychotic medications. The purpose of this study, therefore, was to examine the effects of clozapine on TMS measures of CI and to compare these effects to unmedicated persons with schizophrenia and healthy subjects. We used two TMS inhibitory paradigms: short interval intra-cortical inhibition (SICI) and the cortical silent period (CSP) to evaluate CI in 10 clozapine-treated persons with schizophrenia, 6 unmedicated persons with schizophrenia and 10 healthy subjects. Clozapine-treated persons with schizophrenia had significantly longer CSPs compared with healthy subjects and unmedicated persons with schizophrenia. There were no significant differences in SICI between groups, however, the severity of psychotic symptoms was correlated with reduced SICI across all persons with schizophrenia. Our findings suggest that clozapine treatment is associated with greater CI in persons with schizophrenia and this increase may be related to potentiation of cortical GABAergic receptor mediated inhibitory neurotransmission. Our results also confirm previous findings suggesting that deficits in CI are related to the severity of psychotic symptoms in persons with schizophrenia.
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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".