High‐frequency electroencephalographic oscillations correlate with outcome of epilepsy surgery
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Bibliographic record
Abstract
OBJECTIVE: High-frequency oscillations (HFOs) in the intracerebral electroencephalogram (EEG) have been linked to the seizure onset zone (SOZ). We investigated whether HFOs can delineate epileptogenic areas even outside the SOZ by correlating the resection of HFO-generating areas with surgical outcome. METHODS: Twenty patients who underwent a surgical resection for medically intractable epilepsy were studied. All had presurgical intracerebral EEG (500Hz filter and 2,000Hz sampling rate), at least 12-month postsurgical follow-up, and a postsurgical magnetic resonance imaging (MRI). HFOs (ripples, 80-250Hz; fast ripples, >250Hz) were identified visually during 5 to 10 minutes of slow-wave sleep. Rates and extent of HFOs and interictal spikes in resected versus nonresected areas, assessed on postsurgical MRIs, were compared with surgical outcome (Engel's classification). We also evaluated the predictive value of removing the SOZ in terms of surgical outcome. RESULTS: The mean duration of follow-up was 22.7 months. Eight patients had good (Engel classes 1 and 2) and 12 poor (classes 3 and 4) surgical outcomes. Patients with a good outcome had a significantly larger proportion of HFO-generating areas removed than patients with a poor outcome. No such difference was seen for spike-generating regions or the SOZ. INTERPRETATION: The correlation between removal of HFO-generating areas and good surgical outcome indicates that HFOs could be used as a marker of epileptogenicity and may be more accurate than spike-generating areas or the SOZ. In patients in whom the majority of HFO-generating tissue remained, a poor surgical outcome occurred.
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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) | 0.001 | 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) | 0.000 | 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 it