Anodal Transcranial Direct Current Stimulation Could Modulate Cortical Excitability and the Central Cholinergic System in Akinetic Rigid-Type Parkinson's Disease: Pilot Study
Bibliographic record
Abstract
Background Transcranial direct current stimulation (tDCS) is a non-invasive technique that has been widely studied as an alternative treatment for Parkinson's disease (PD). However, its clinical benefit remains unclear. In this study, we aimed to investigate the effect of tDCS on the central cholinergic system and cortical excitability in mainly akinetic rigid-type patients with PD. Methods In total, 18 patients with PD were prospectively enrolled and underwent 5 sessions of anodal tDCS on the M1 area, which is on the contralateral side of the dominant hand. We excluded patients with PD who had evident resting tremor of the hand to reduce the artifact of electrophysiologic findings. We compared clinical scales reflecting motor, cognitive, and mood symptoms between pre- and post-tDCS. Additionally, we investigated the changes in electrophysiologic parameters, such as short latency afferent inhibition (SAI) (%), which reflects the central cholinergic system. Results The United Parkinson's Disease Rating Scale Part 3 (UPDRS-III), the Korean-Montreal Cognitive Assessment (MoCA-K), and Beck Depression Inventory (BDI) scores were significantly improved after anodal tDCS (p < 0.01, p < 0.01, and p < 0.01). Moreover, motor evoked potential amplitude ratio (MEPAR) (%) and integrated SAI showed significant improvement after tDCS (p < 0.01 and p < 0.01). The mean values of the change in integrated SAI (%) were significantly correlated with the changes in UPDRS-III scores; however, the MoCA-K and BDI scores did not show differences. Conclusions Anodal tDCS could influence the central cholinergic system, such as frontal cortical excitability and depression in PD. This mechanism could underlie the clinical benefit of tDCS in patients with 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".