Cortical thickness analysis in operculo-insular epilepsy
Bibliographic record
Abstract
In temporal lobe epilepsy (TLE), advanced neuroimaging techniques reveal anomalies extending beyond the temporal lobe such as thinning of fronto-central cortices. Operculo-insular epilepsy (OIE) is an under-recognized and poorly characterized condition with the potential of mimicking TLE. In this work, we investigated insular and extra-insular cortical thickness (CT) changes in OIE. All participants (14 patients with refractory OIE, 9 age- and sex-matched patients with refractory TLE and 26 healthy controls) underwent a T1-weighted acquisition on a 3 T MRI. Anatomical images were processed with Advanced Normalization Tools. Between-group analysis of CT was performed using a two-sided t-test (threshold of p < 0.05 after correction for multiple comparisons; cut-off threshold of 250 voxels) between (i) patients with OIE vs TLE, and (ii) patients with OIE vs healthy controls. Significant widespread thinning was observed in OIE patients as compared with healthy controls mainly in the ipsilateral insula, peri-rolandic region, orbito-frontal area, mesiotemporal structures and lateral temporal neocortex. Contralateral cortical shrinkage followed a similar albeit milder and less diffuse pattern. The CT of OIE patients was equal or reduced relative to the TLE group for every cortical region analyzed. Thinning was observed diffusely in OIE patients, predominantly inboth insulae and the ipsilateral occipito-temporal area. Our results reveal structural anomalies extending beyond the operculo-insular area in OIE.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".