Motor cortex plasticity in Parkinson's disease and levodopa-induced dyskinesias
Bibliographic record
Abstract
Experimental models of Parkinson's disease have demonstrated abnormal synaptic plasticity in the corticostriatal system, possibly related to the development of levodopa-induced dyskinesias (LID). We tested the hypothesis that LID in Parkinson's disease is associated with aberrant plasticity in the human motor cortex (M1). We employed the paired associative stimulation (PAS) protocol, an experimental intervention involving transcranial magnetic stimulation (TMS) and median nerve stimulation capable of producing long-term potentiation (LTP) like changes in the sensorimotor system in humans. We studied the more affected side of 16 moderately affected patients with Parkinson's disease (9 dyskinetic, 7 non-dyskinetic) and the dominant side of 9 age-matched healthy controls. Motor-evoked potential (MEP) amplitudes and cortical silent period (CSP) duration were measured at baseline before PAS and for up to 60 min (T0, T30 and T60) after PAS in abductor pollicis brevis (APB) and abductor digiti minimi (ADM) muscles. PAS significantly increased MEP size in controls (+74.8% of baseline at T30) but not in patients off medication (T30: +0.07% of baseline in the non-dyskinetic, +27% in the dyskinetic group). Levodopa restored the potentiation of MEP amplitudes by PAS in the non-dyskinetic group (T30: +64.9% of baseline MEP) but not in the dyskinetic group (T30: -9.2% of baseline). PAS prolonged CSP duration in controls. There was a trend towards prolongation of CSP in the non-dyskinetic group off medications but not in the dyskinetic group. Levodopa did not restore CSP prolongation by PAS in the dyskinetic group. Our findings suggest that LTP-like plasticity is deficient in Parkinson's disease off medications and is restored by levodopa in non-dyskinetic but not in dyskinetic patients. Abnormal synaptic plasticity in the motor cortex may play a role in the development of LID.
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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".