Concomitant improvement in anti-saccade success rate and postural instability gait difficulty after rTMS treatment for Parkinson’s disease
Bibliographic record
Abstract
Parkinson's disease (PD) is a progressive neurological disorder characterised by motor and non-motor deficits. Repetitive transcranial magnetic stimulation (rTMS) over the bilateral primary motor cortex at a high frequency (5 Hz or higher) is reported to be a potential treatment of PD. We aimed to assess the effect of rTMS on eye movement control in patients with PD in their 'on' state. We enrolled 14 patients with PD and assessed motor symptoms (Movement Disorder Society-Sponsored Unified Parkinson's Disease Rating Scale; MDS-UPDRS) and eye movement performances (visually guided saccades, volitional anti-saccades, and small involuntary saccades during fixation) at baseline and after administering bilateral 10 Hz rTMS on leg region of the motor cortex. We confirmed that rTMS improved the MDS-UPDRS motor scores and found that rTMS improved the anti-saccade success rate, which requires adequate inhibition of the reflexive response. The improvement in anti-saccade success rate was correlated with that of the postural instability gait difficulty (PIGD) sub-scores of MDS-UPDRS and lower baseline Japanese version of the Montreal Cognitive Assessment scores. This result is consistent with previous findings that PIGD and inhibitory control deficits share common brain dysfunctions in PD. rTMS may alleviate dysfunctions of that circuit and have a clinical effect.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".