Preictal surrender of post–spike slow waves to spike‐related high‐frequency oscillations (80–200 Hz) is associated with seizure initiation
Bibliographic record
Abstract
OBJECTIVE: Spike and slow waves consist of a "spike" including high-frequency oscillations (HFOs), which are linked to epileptogenicity and a "post-spike slow wave (PSS)" related to inhibitory activity. The aim of this study was to elucidate the spatiotemporal relationship between spike-related HFOs and PSS in patients with focal cortical dysplasia (FCD) type II. METHODS: We studied 10 pediatric patients with FCD type II, who underwent extraoperative video-electroencephalography (EEG). We selected spike and slow waves, which included HFOs (80-200 Hz), and performed spike peak-locked averaging 10 times during both 30 s interictal (>1 h apart from seizures) and 30 s preictal periods. We calculated the power of spike-related HFOs and PSS during both periods for the following three areas: (1) inside the seizure-onset zone (SOZ), (2) inside the resection area (RA) but outside SOZ (RA-SOZ), and (3) outside the RA. Between the interictal and preictal periods we performed correlation (Spearman's coefficient) and simple linear regression analyses comparing HFO and PSS power within each area. RESULTS: A total of 1,614 averaged spike and slow waves were analyzed during both periods. During the interictal periods, there were significant positive correlations between HFO and PSS power in all areas (inside SOZ, r = 0.568; RA-SOZ, r = 0.700; outside RA, r = 0.320). During the preictal periods, the correlation became weaker inside SOZ (r = 0.149) and remained unchanged both inside the RA-SOZ (r = 0.704) and outside RA (r = 0.346). From the interictal to preictal period, the slope (ΔPSS power/ΔHFO power) of the simple regression line decreased inside SOZ (0.349 to 0.051) but increased in RA-SOZ (0.534 to 0.734) and outside RA (0.267 to 0.435). SIGNIFICANCE: Relative power reduction of PSS to spike-related HFOs in SOZ is relevant for seizure initiation. Our analysis will contribute to future studies of seizure prediction and distinction between pathologic and physiologic HFOs. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".