Subthalamic Nucleus Deep Brain Stimulation: An Invaluable Role for MER
Bibliographic record
Abstract
INTRODUCTION: Subthalamic nucleus (STN) deep brain stimulation (DBS) is currently the main surgical procedure for medically refractory Parkinson's disease. The benefit of intra-operative microelectrode recording (MER) for the purpose of neurophysiological localization and mapping of the STN continues to be debated. METHODS: A retrospective review of the charts and operative reports of all patients receiving STN DBS implantation for Parkinson's disease at our institution from January 2004 to March 2011 was done. RESULTS: Data from 43 of 44 patients with Parkinson's disease treated with STN DBS were reviewed. The average number of tracts on the left was 2.4, versus 2.3 on the right. The average dorsal and ventral anatomical boundaries of the STN based on Schaltenbrand's Stereotactic Atlas were estimated to be at -5.0 mm above and +1.4 mm below target respectively. The average dorsal and ventral boundaries of the STN using MER were -2.6 mm above and +2.0 mm below target respectively. The average dorsal-ventral distance of the STN as predicted by Stereotactic Atlas was 6.4 mm, compared to 4.6 mm as determined by MER. MER demonstrated the average dorsal and ventral boundaries on the left side were -2.6 mm and +2.2 mm from target respectively, while the average dorsal and ventral boundaries on the right side were -2.5 mm and +1.8 mm from target respectively with MER. CONCLUSIONS: MER in STN DBS surgery demonstrated measurable difference between stereotactic atlas/MRI STN target and neurophysiologic STN localization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".