L-Dopa Medication in Parkinson's Disease Restores Activity in the Motor Cortico-Striatal Loop but Does Not Modify the Cognitive Network
Bibliographic record
Abstract
BACKGROUND: The goal of this study was to evaluate the effects of L-Dopa medication in Parkinson's disease (PD) on brain activation during the performance of a set-shifting task. Using fMRI, we have previously studied the patterns of activity observed in patients with PD after overnight removal of dopaminergic medication compared with control participants during the performance of different stages of the Wisconsin Card Sorting Task (WCST). The results revealed decreased cortical activity in the PD group compared to controls in the conditions that significantly required striatum, while increased cortical activity was observed when striatum was not involved. However, the effect of dopaminergic medication in PD patients on those patterns of activity has not yet been studied. METHODOLOGY/PRINCIPAL FINDINGS: Here, eleven PD patients at early stage of the disease taking L-Dopa medication were recruited and underwent two fMRI sessions while performing the WCST: one session while taking their normal dose of medication and the other following overnight dopaminergic medication withdrawal. We found that L-dopa medication helped restoring a normal pattern of activity when matching and not planning was required, by increasing cortical activity in the premotor cortex. This effect was even stronger in the motor loop, i.e. when the putamen was required for controls, when matching following negative feedback. However, the medication did not change the pattern of activity in conditions relying primarily on a cognitive loop, i.e. when the caudate nucleus was required. CONCLUSIONS/SIGNIFICANCE: These studies provide explanation at the neural level regarding the relatively poor effects of L-Dopa on the cognitive deficits observed 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 | 0.000 |
| 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".