Intrahemispheric reorganization of language in children with medically intractable epilepsy of the left hemisphere
Bibliographic record
Abstract
We investigated language representation in nine children (six male, three female; 5.6-17.7 years of age) who underwent surgical treatment of medically intractable epilepsy of the left hemisphere. Although interhemispheric reorganization has been previously documented in similar groups, this is the first study to systematically evaluate possible intrahemispheric effects of early insult. All cases had left hemisphere seizure foci and underwent extraoperative stimulation mapping (ESM) for language localization prior to receiving cortical resections. To compare ESM findings across subjects and to assess intrahemispheric reorganization, we developed a novel coregistration technique whereby independent raters plotted two-dimensional (2D) ESM findings in 3D standard space. Expressive language sites identified with ESM were compared with a structural probability map of pars opercularis, or Broca's area. The average difference between independent raters' estimates of 28 language sites was 3.9 mm (SD = 2.0), indicating excellent agreement; the coregistration procedure permitted assessment of 2D ESM findings in 3D standard space. We observed language sites in regions substantially anterior and superior to canonical Broca's area, possibly reflecting intrahemispheric reorganization. Findings suggest that left hemisphere insult in young children may result in anterior displacement of language within the frontal cortex.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".