P.026 Focal DBS of Posterior Cingulate Cortex for Refractory Nonlesional Epilepsy: A Case Report
Bibliographic record
Abstract
Background: Deep brain stimulation for epilepsy is becoming an effective option for the treatment of refractory epilepsy. This is the case of a 19-year-old male patient who has had refractory seizures since 2.5 years old. Seizures occur up to 100 times per day, including gelastic, complex partial, and generalized tonic-clonic types. Methods: Continuous video-EEG monitoring, technetium 99 m ECD SPECT, PET-CT and 3T MRI are used for localization. Depth electrodes are implanted in right frontal orbital, cingulate and lateral frontal regions. Results: Video-EEG records 79 seizures arising from the right frontocentral region. Clinically, patient assumes a fencing posture, with left arm extension. Some seizures undergo secondary generalization. SPECT reveals subtle asymmetric hyperperfusion in right mesial frontal area, while PET-CT and MRI do not show focal lesion(s).Stereo-EEG recording and stimulation confirm seizure onset and trigger zone in the premotor cingulate posterior region. Treatment with stimulation in this region at 130-150 Hz, 4-5 mA, and pulse duration 0.1 ms reduces seizure frequency from 100/day to 3/week. Seizures last only 2-3 seconds, without postictal confusion leading to improvements in neuropsychological function. AED dosages are not reduced. Conclusions: Successful intracranial EEG localization of otherwise non-lesional non-resectable seizure focus permits the use of deep brain stimulation that effectively reduces refractory seizure frequency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| 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".