Bilateral perisylvian ulegyria: Clinicopathological study of patients presenting with pseudobulbar palsy and epilepsy
Bibliographic record
Abstract
Structural abnormalities related with pseudobulbar palsy have been gaining attention because of their characteristic symptoms and unique pathogenesis. We present five cases of bilateral perisylvian ulegyria (BPU) presenting epilepsy and pseudobulbar palsy with pathogenesis different from previously reported syndromes. All patients showed medically intractable seizures, complex partial seizures with secondary generalization and clinical symptoms of pseudobulbar palsy, including dysarthria, limitation of tongue movement and drooling. MRI revealed BPU in all patients, and BPU associated with hippocampal sclerosis in four patients. Intracranial EEG recording with subdural grip and stripe was helpful for localizing the area of ictal generation. Resective surgeries, including the temporal lobe, central area and parietal lobe, were performed depending on the localizing information. The surgical outcome was favorable after 9.8 years of follow-up. Characteristic features of ulegyria were confirmed on pathological examination. Ulegyria is considered to be another important perinatal or postnatal structural abnormality which can explain the etiological heterogeneity for pseudobulbar palsy, which results from bilateral perisylvian lesions. Awareness of this disorder can provide a useful strategy for evaluation and treatment which differs from that in perisylvian polymicrogyria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".