Asymmetrical Effect of Levodopa on the Neural Activity of Motor Regions in PD
Bibliographic record
Abstract
Parkinson's disease (PD) is a neurodegenerative illness often characterized by asymmetrical symptoms. However, the reason for this asymmetry and the cerebral correlates underlying symptom asymmetry are still not well understood. Furthermore, the effects of levodopa on the cerebral correlates of disease asymmetry have not been investigated. In this study, right-handed PD patients performed self-initiated, externally triggered and repetitive control finger movements with both their right and left hands during functional magnetic resonance imaging (fMRI) to investigate asymmetrical effects of levodopa on the hemodynamic correlates of finger movements. Patients completed two experimental sessions OFF and ON medication after a minimum of 12 hours medication withdrawal. We compared the effect of levodopa on the neural activation patterns underlying the execution of both the more affected and less affected hand for self-initiated and externally triggered movements. Our results show that levodopa led to larger differences in cerebral activity for movements of the more affected, left side: there were significant differences in activity after levodopa administration in regions of the motor cortico-striatal network when patients performed self-initiated and externally triggered movements with their left hand. By contrast, when patients used their right hand, levodopa led to differences in cerebellar activity only. As our patients were affected more severely on their left side, we propose that levodopa may help provide additional dopaminergic input, improving movements for the more severely affected side. These results suggest that the impact of reduced dopamine in the cortico-striatal system and the action of levodopa is not symmetrical.
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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) | 0.000 | 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".