Phase‐amplitude coupling between interictal high‐frequency activity and slow waves in epilepsy surgery
Bibliographic record
Abstract
Abstract Objective We hypothesized that the modulation index ( MI ), a summary measure of the strength of phase‐amplitude coupling between high‐frequency activity (>150 Hz) and the phase of slow waves (3‐4 Hz), would serve as a useful interictal biomarker for epilepsy presurgical evaluation. Methods We investigated 123 patients who underwent focal cortical resection following extraoperative electrocorticography recording and had at least 1 year of postoperative follow‐up. We examined whether consideration of MI would improve the prediction of postoperative seizure outcome. MI was measured at each intracranial electrode site during interictal slow‐wave sleep. We compared the accuracy of prediction of patients achieving International League Against Epilepsy class 1 outcome between the full multivariate logistic regression model incorporating MI in addition to conventional clinical, seizure onset zone ( SOZ ), and neuroimaging variables, and the reduced logistic regression model incorporating all variables other than MI . Results Ninety patients had class 1 outcome at the time of most recent follow‐up (mean follow‐up = 5.7 years). The full model had a noteworthy outcome predictive ability, as reflected by regression model fit R 2 of 0.409 and area under the curve ( AUC ) of receiver operating characteristic plot of 0.838. Incomplete resection of SOZ ( P < 0.001), larger number of antiepileptic drugs at the time of surgery ( P = 0.007), and larger MI in nonresected tissues relative to that in resected tissue ( P = 0.020) were independently associated with a reduced probability of class 1 outcome. The reduced model had a lower predictive ability as reflected by R 2 of 0.266 and AUC of 0.767. Anatomical variability in MI existed among nonepileptic electrode sites, defined as those unaffected by magnetic resonance imaging lesion, SOZ , or interictal spike discharges. With MI adjusted for anatomical variability, the full model yielded the outcome predictive ability of R 2 of 0.422, AUC of 0.844, and sensitivity/specificity of 0.86/0.76. Significance MI during interictal recording may provide useful information for the prediction of postoperative seizure outcome.
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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 | 0.001 | 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 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".