Levodopa influences striatal activity but does not affect cortical hyper‐activity in Parkinson’s disease
Bibliographic record
Abstract
Motor studies of Parkinson's disease (PD) have shown cortical hypo-activity in relation to nigrostriatal dopamine depletion. Cognitive studies also identified increased cortical activity in PD. We have previously suggested that the hypo-activity/hyper-activity patterns observed in PD are related to the striatal contribution. Tasks that recruit the striatum in control participants are associated with cortical hypo-activity in patients with PD, whereas tasks that do not result in cortical hyper-activity. The putamen, a structure affected by the neurodegeneration observed in PD, shows increased activation for externally-triggered (ET) and self-initiated (SI) movements. The first goal of this study was to evaluate the effect of levodopa on the putamen's response to ET and SI movements. Our second goal was to assess the effect of levodopa on the hypo-activity/hyper-activity patterns in cortical areas. Patients with PD on and off levodopa and healthy volunteers performed SI, ET and control finger movements during functional magnetic resonance imaging. Healthy participants displayed significant differences in putamen activity in ET and SI movements. These differences were reduced in patients off medication, with non-task-specific increases in activity after levodopa administration. Furthermore, the ventrolateral prefrontal cortex showed significant increases in activity during SI movements in healthy controls, whereas it was hypo-active in PD. This region showed significantly increased activity during ET movements in patients off medication. Levodopa had no effect on this discrepancy. Our results suggest that dopamine replacement therapy has a non-task-specific effect on motor corticostriatal regions, and support the hypothesis that increases and decreases in cortical activity in PD are related to the mesocortical dopamine pathway imbalance.
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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".