Deep brain stimulation: potential for neuroprotection
Bibliographic record
Abstract
Over the last two decades there has been an exponential rise in the number of patients receiving deep brain stimulation (DBS) to manage debilitating neurological symptoms in conditions such as Parkinson's disease, essential tremor, and dystonia. Novel applications of DBS continue to emerge including treatment of various psychiatric conditions (e.g. obsessive-compulsive disorder, major depression) and cognitive disorders such as Alzheimer's disease. Despite widening therapeutic applications, our understanding of the mechanisms underlying DBS remains limited. In addition to modulation of local and network-wide neuronal activity, growing evidence suggests that DBS may also have important neuroprotective effects in the brain by limiting synaptic dysfunction and neuronal loss in neurodegenerative disorders. In this review, we consider evidence from preclinical and clinical studies of DBS in Parkinson's disease, Alzheimer's disease, and epilepsy that suggest chronic stimulation has the potential to mitigate neuronal loss and disease progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".