A – 115 Verbal learning and memory in spinocerebellar ataxia type 12 (SCA12): Preliminary findings
Bibliographic record
Abstract
Abstract Objective Spinocerebellar ataxia type 12 (SCA12) is a rare neurodegenerative movement disorder highly prevalent in an ethnic community in India. Prior studies have suggested that cognitive domains—particularly memory—may be compromised. We aim to compare patterns of learning and memory between SCA12 patients and healthy controls. Method We recruited 11 genetically confirmed SCA12 patients through a neurology hospital in eastern India. 12 controls were matched for age, gender, community, and years of education. We administered a neuropsychological battery to all participants through home visits. We evaluated global cognitive function using the Montreal Cognitive Assessment (MoCA), and verbal learning and memory using the adapted CERAD word list learning task. Results MoCA scores were not significantly different between SCA12 patients and healthy controls although the patients tended to have a lower score. SCA12 patients showed a significant impairment in learning across 3 trials. Two-way analysis of variance (ANOVA) showed a significant group effect (p=0.03) and trial effect (p< 0.0001). Bonferroni’s multiple-comparisons test showed that both patients and controls recalled a similar number of words in T1 (p=0.4) and T3 (p=0.4), but controls recalled a significantly greater number of words in T2 (p=0.02). Importantly, while delayed recall continued to be poorer in SCA12 patients, delayed recognition was not affected (Two-tailed unpaired t-test, for recall: p=0.03, for recognition: p=0.3). Conclusion Our preliminary results indicate that verbal learning and recall, but not recognition, are impaired in SCA12 patients, suggesting that initial encoding remains relatively preserved. Further data collection and subgroup analysis may reveal differences based on gender or educational attainment.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".