Functional MRI of the pre-ictal state
Bibliographic record
Abstract
The mechanisms underlying the transition from interictal to ictal states are poorly understood. Non-linear mathematical analysis of EEG frequency components has confirmed the presence of a pre-ictal state in focal epilepsy. We report on functional MRI (fMRI) analysis of the pre-ictal state in three patients with intractable focal epilepsy. Each subject had a typical partial seizure in the scanner while continuous blood oxygen level dependent (BOLD) fMRI images were acquired. The pre-ictal BOLD changes were first analysed by statistically comparing BOLD signals of two one-minute blocks. Further examination of the full time course was then performed. Each patient showed highly significant, focal BOLD signal changes. In Patient 1, a striking pre-ictal BOLD signal increase was seen over the region of the seizure focus identified on complementary epilepsy investigations. No significant BOLD signal decreases were observed. Patient 2 showed widespread pre-ictal BOLD increase contralateral to the presumed seizure focus, as well as a focal BOLD decrease near the presumed seizure focus. In Patient 3, pre-ictal BOLD increase was co-localized with the site of hyperperfusion seen on ictal single photon emission computed tomography (SPECT). However, this was contralateral to the seizure focus localization based on seizure symptomatology. No significant BOLD decreases were seen. The time course data in each patient studied showed change of the BOLD signal several minutes before the onset of the seizure. Highly significant BOLD fMRI signal changes occur before the onset of seizures, supporting the presence of a pre-ictal state. These changes can be localized to the site of the presumed seizure focus, as well as to other brain regions, suggesting that the pre-ictal BOLD signal changes and their underlying mechanisms are complex.
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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 | 0.000 |
| 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) | 0.000 | 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".