Exploring Magnetic and Electrical Brain Stimulation in Parkinsonian Dyskinetic Monkeys
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) chronic L-Dopa treatment often triggers motor complications, such as L-Dopa-induced dyskinesias (LID). LID are reported to be associated with abnormal glutamatergic activity between the striatum and primary motor cortex (M1), resulting in M1 hyperactivation. Beneficial noninvasive brain stimulation (NIBS) paradigms were reported to normalize glutamatergic activity. The objective of the present study was thus to set up a NIBS paradigm in parkinsonian monkeys to investigate motor behavior under basal conditions and with L-Dopa treatment-inducing dyskinesias. METHODS: monkey models of PD, allowing us to monitor the administration of NIBS and drugs. NIBS used were inhibitory protocols, that is, cathodal transcranial direct current stimulation (c-tDCS) and continuous theta-burst stimulation (cTBS). A procedure of three weeks was developed to progressively acclimate animals to the experimental conditions, equipment and noise of c-tDCS and cTBS before stimulating them with either vehicle or L-Dopa. RESULTS: One session of c-tDCS with L-Dopa yielded no effect, whereas five sessions briefly reduced LID but decreased the duration of L-Dopa anti-PD effects. cTBS alone improved (decreased) parkinsonian scores as compared to sham stimulation or vehicle alone. Two sessions of cTBS with L-Dopa decreased LID without affecting L-Dopa anti-PD effects. CONCLUSION: This is the first study testing c-tDCS and cTBS on the motor behavior of MPTP dyskinetic monkeys. As compared to medicated patients, MPTP monkeys offer the opportunity to evaluate NIBS after-effects in drug-free and LID conditions, which are critical in the search for new PD treatment.
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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".