Operculo-Insular Epilepsy: Scalp and Intracranial Electroencephalographic Findings
Bibliographic record
Abstract
PURPOSE: Operculo-insular seizures are heterogeneous and may resemble seizures originating from the temporal, frontal, or parietal lobe. Although surface and invasive EEG recordings are often necessary to detect operculo-insular seizures, electrophysiological features of operculo-insular epilepsies remain poorly characterized. This study describes the EEG findings of patients with operculo-insular epilepsy. METHODS: We reviewed electrophysiological data of all patients (n = 9) with operculo-insular seizures revealed by intracranial EEG and for whom operculo-insular epilepsy was confirmed by good seizure outcome after resective or radiosurgery at our center between 2005 and 2013. Patients were divided according to whether their seizure focus involved the anterior (group 1; n = 4) or posterior (group 2; n = 5) portion of the insula. RESULTS: Interictal scalp EEG was lateralizing and showed distinct topographical spike patterns between groups: frontal and temporal in group 1, temporal in group 2. Intracranial recordings showed abundant spikes limited to the operculo-insular region or involving distant areas in the frontal/temporal (group 1) and temporal/parietal lobes (group 2). Ictal intracranial EEG revealed discharges limited to the insula or simultaneously involving extrainsular contacts at onset, notably the orbitofrontal cortex (group 1) and the frontal and parietal opercula (group 2), and propagating to the frontal and temporal lobes in group 1 and to parietal and temporal lobes in group 2. CONCLUSIONS: Spike distribution and seizure propagation in operculo-insular epilepsy follows an anterior-to-posterior pattern mirroring an anterior or posterior insular focus localization. When presented with frontal and/or temporal epileptiform abnormalities, an operculo-insular focus should be considered.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".