The hemodynamic response to interictal epileptic discharges localizes the seizure‐onset zone
Bibliographic record
Abstract
OBJECTIVE: Intracranial electroencephalography (EEG), performed presurgically in patients with drug-resistant and difficult-to-localize focal epilepsy, samples only a small fraction of brain tissue and thus requires strong hypotheses regarding the possible localization of the epileptogenic zone. EEG/fMRI (functional magnetic resonance imaging), a noninvasive tool resulting in hemodynamic responses, could contribute to the generation of these hypotheses. This study assessed how these responses, despite their interictal origin, predict the seizure-onset zone (SOZ). METHODS: We retrospectively studied 37 consecutive patients who underwent stereo-EEG (SEEG) and EEG/fMRI that resulted in significant hemodynamic responses. Hemodynamic response maps were co-registered to postimplantation anatomic imaging, allowing inspection of these responses in relation to SEEG electrode's location. The area containing the most significant t-value (primary cluster) explored with an electrode was assessed for concordance with SEEG-defined SOZ. Discriminant analysis was performed to distinguish the primary clusters having a high probability of localizing the SOZ. RESULTS: Thirty-one patients had at least one study with primary cluster explored with an electrode, and 24 (77%) had at least one study with primary cluster concordant with the SOZ. Each patient could have multiple types of interictal discharge and therefore multiple studies. Among 59 studies from the 37 patients, 44 had a primary cluster explored with an electrode and 30 (68%) were concordant with the SOZ. Discriminant analysis showed that the SOZ is predictable with high confidence (>90%) if the primary cluster is highly significant and if the next significant cluster is much less significant or absent. SIGNIFICANCE: The most significant hemodynamic response to interictal discharges delineates the subset of the irritative zone that generates seizures in a high proportion of patients with difficult-to-localize focal epilepsy. EEG/fMRI generates responses that are valuable targets for electrode implantation and may reduce the need for implantation in patients in whom the most significant response satisfies the condition of our discriminant analysis.
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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) | 0.000 | 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) | 0.001 | 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 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".