Evaluation of Cognition and Cortical Excitability in Huntington’s Disease
Bibliographic record
Abstract
BACKGROUND: Recent advances in neurophysiological techniques have contributed to our understanding of the pathophysiology of Huntington's disease (HD). Studies of the motor cortical excitability and central motor pathways have shown variable results. OBJECTIVES: Our aims were to evaluate the cortical excitability changes in HD using transcranial magnetic stimulation (TMS) and correlate the changes with cognitive impairment. METHODS: The study included 32 HD patients and 30 age- and gender-matched controls. The demographic and clinical profiles of the patients were recorded. All subjects were evaluated by TMS and resting motor threshold (RMT), central motor conduction time (CMCT), silent period (SP), short-interval intracortical inhibition (SICI), and intracortical facilitation were determined. A battery of neuropsychological tests was administered to all subjects. RESULTS: The mean age of the patients was 42.1±14.1 years, and that of controls 39.4±12.4 years (p=0.61). There was no significant difference in RMT and CMCT between the two groups. There was a mild prolongation of the contralateral SP in HD, but it was not significant. SICI was significantly reduced in HD (p<0.0001). A significant impairment in attention, verbal fluency, executive function, visuospatial function, learning, and memory was observed in HD patients. However, there was no correlation between cortical excitability changes and cognitive impairment. CONCLUSIONS: TMS is a valuable method of evaluating cortical excitability changes in HD. These patients have reduced SICI and significant impairment of cognition in multiple domains.
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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".