Alcohol improves cerebellar learning deficit in myoclonus–dystonia: A clinical and electrophysiological investigation
Bibliographic record
Abstract
OBJECTIVE: To characterize neurophysiological subcortical abnormalities in myoclonus-dystonia and their modulation by alcohol administration. METHODS: Cerebellar associative learning and basal ganglia-brainstem interaction were investigated in 17 myoclonus-dystonia patients with epsilon-sarcoglycan (SGCE) gene mutation and 21 age- and sex-matched healthy controls by means of classical eyeblink conditioning and blink reflex recovery cycle before and after alcohol intake resulting in a breath alcohol concentration of 0.08% (0.8g/l). The alcohol responsiveness of clinical symptoms was evaluated by 3 blinded raters with a standardized video protocol and clinical rating scales including the Unified Myoclonus Rating Scale and the Burke-Fahn-Marsden Dystonia Rating Scale. RESULTS: Patients showed a significantly reduced number of conditioned eyeblink responses before alcohol administration compared to controls. Whereas the conditioning response rate decreased under alcohol intake in controls, it increased in patients (analysis of variance: alcohol state × group, p = 0.004). Blink reflex recovery cycle before and after alcohol intake did not differ between groups. Myoclonus improved significantly after alcohol intake (p = 0.016). The severity of action myoclonus at baseline correlated negatively with the conditioning response in classical eyeblink conditioning in patients. INTERPRETATION: The combination of findings of reduced baseline acquisition of conditioned eyeblink responses and normal blink reflex recovery cycle in patients who improved significantly with alcohol intake suggests a crucial role of cerebellar networks in the generation of symptoms in these patients. Ann Neurol 2017;82:543-553.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".