Effect of subthalamic nucleus deep brain stimulation on dual-task cognitive and motor performance in isolated dystonia
Bibliographic record
Abstract
OBJECTIVE: Subthalamic nucleus (STN) deep brain stimulation (DBS) can improve motor complications of Parkinson's disease (PD) but may worsen specific cognitive functions. The effect of STN DBS on cognitive function in dystonia patients is less clear. Previous reports indicate that bilateral STN stimulation in patients with PD amplifies the decrement in cognitive-motor dual-task performance seen when moving from a single-task to dual-task paradigm. We aimed to determine if the effect of bilateral STN DBS on dual-task performance in isolated patients with dystonia, who have less cognitive impairment and no dementia, is similar to that seen in PD. METHODS: Eight isolated predominantly cervical patients with dystonia treated with bilateral STN DBS, with average dystonia duration of 10.5 years and Montreal Cognitive Assessment score of 26.5, completed working memory (n-back) and motor (forced-maintenance) tests under single-task and dual-task conditions while on and off DBS. RESULTS: A multivariate, repeated-measures analysis of variance showed no effect of stimulation status (On vs Off) on working memory (F=0.75, p=0.39) or motor function (F=0.22, p=0.69) when performed under single-task conditions, though as working memory task difficulty increased, stimulation disrupted the accuracy of force-tracking. There was a very small worsening in working memory performance (F=9.14, p=0.019) when moving from single-task to dual-tasks when using the 'dual-task loss' analysis. CONCLUSIONS: This study suggests the effect of STN DBS on working memory and attention may be much less consequential in patients with dystonia than has been reported in PD.
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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) | 0.001 | 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) | 0.001 | 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".