Deep brain stimulation electrodes used for staged lesion within the basal ganglia: experimental studies for parameter validation
Bibliographic record
Abstract
OBJECT: Deep brain stimulation (DBS) has been shown to be an effective treatment for various types of movement disorders. High-frequency stimulation is applied to specific brain targets through an implanted quadripolar lead connected to a pulse generator. These leads can be used for creating lesions in the brain. The experimental study reported here was designed to examine the electrical parameters that could be used to create reproducible therapeutic lesions in the brain. METHODS: Egg whites were used to measure the relationship between the electrical parameters (current and voltage) applied through the DBS electrode and the size of coagulum. The authors measured current spread from the electrode contact used for lesioning to the adjacent contact. Similar studies were performed in the pallidum or the thalamus of human cadavers. Modeling of the lesion size was performed with simulation of current density and temperature. The ultrastructure of the electrodes after lesioning was verified by electron microscopy. RESULTS: Coagulation size increased with time but reached a plateau after 30 seconds. For a given set of electrical parameters, reproducibility of the size of lesions was high. Using constant voltage, lesions were larger in egg whites than in cadaveric brains with a mean length of 5 +/- 0.6 mm in egg whites at 40 V, 125 mA, impedance 233 Omega; and 4.0 +/- 0.8 mm in cadavers at 40 V, 38 mA, impedance 1333 Omega. Computer modeling indicated negligible current flow to the adjacent, unused electrodes. The electrodes showed no structural alterations on scanning electron microscopy after more than 200 lesions. CONCLUSIONS: Results of this study demonstrate that DBS electrodes can be used to generate lesions reproducibly in the brain. The choice of lesioning parameters must take into account differences in impedance between the test medium (egg whites) and the human brain parenchyma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".