Modulating inhibitory synaptic plasticity to restore basal ganglia dynamics in Parkinson's disease
Bibliographic record
Abstract
Parkinson's disease is characterized, in part, by hypoactivity of direct pathway inhibitory projections from striatum to the globus pallidus internus (GPi) and indirect pathway inhibitory projections from globus pallidus externus (GPe) to the subthalamic nucleus (STN). In people with Parkinson's disease (n = 32), we explored the potential use of intracranial stimulation for eliciting long-term potentiation (LTP) of these underactive pathways to produce improvement of symptoms that persist beyond stimulation cessation. During GPi deep brain stimulation (DBS) surgery, we found strong evidence (P < 0.05; BF10 > 10) of increased amplitudes of hand movements and striato-GPi evoked potentials before versus after high-frequency microstimulation. In a small sample of outpatients with sensing-enabled GPi-DBS, we found anecdotal evidence (P < 0.10; BF10 > 1) of improved hand movements and attenuated beta frequency oscillations. In STN, enduring behavioural effects, potentiation of GPe-STN projections (intraoperative), and decreases to beta oscillations (extraoperative) were not observed. Our findings support that LTP-like effects in GPi may produce motor improvements that extend beyond stimulation cessation, while the lack of effects in STN suggests the need for optimizing stimulation paradigms for effective LTP induction. These findings nevertheless highlight the potential of LTP-based strategies for sustained therapeutic benefits, which may be useful for mitigating DBS side-effects and optimizing battery usage.
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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".