Cerebellar motor learning deficits in medicated and medication-free men with recent-onset schizophrenia
Bibliographic record
Abstract
BACKGROUND: The notion that cerebellar deficits may underlie clinical symptoms in people with schizophrenia is tested by evaluating 2 forms of cerebellar learning in patients with recent-onset schizophrenia. A potential medication effect is evaluated by including patients with or without antipsychotics. METHODS: We assessed saccadic eye movement adaptation and eyeblink conditioning in men with recent-onset schizophrenia who were taking antipsychotic medication or who were antipsychotic-free and in age-matched controls. RESULTS: We included 39 men with schizophrenia (10 who were taking clozapine, 16 who were taking haloperidol and 13 who were antipsychotic-free) and 29 controls in our study. All participants showed significant saccadic adaptation. Adaptation strength did not differ between healthy controls and men with schizophrenia. The speed of saccade adaptation, however, was significantly lower in men with schizophrenia. They showed a significantly lower increase in the number of conditioned eyeblink responses. Over all experiments, no consistent effects of medication were observed. These outcomes did not correlate with age, years of education, psychopathology or dose of antipsychotics. LIMITATIONS: As patients were not randomized for treatment, an influence of confounding variables associated with medication status cannot be excluded. Individual patients also varied along the schizophrenia spectrum despite the relative homogeneity with respect to onset of illness and short usage of medication. Finally, the relatively small number of participants may have concealed effects as a result of insufficient statistical power. CONCLUSION: We found several cerebellar learning deficits in men with schizophrenia that we cannot attribute to the use of antipsychotics. Although this finding, combined with the fact that deficits are already present in patients with recent-onset schizophrenia, could suggest that cerebellar impairments are a trait deficit in people with schizophrenia. This should be confirmed in longitudinal studies.
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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) | 0.002 | 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".