Atypical language lateralization in patients with left hippocampal sclerosis: does the hippocampus affect language lateralization?
Bibliographic record
Abstract
AIM: To provide information related to atypical language activations (right or bilateral) in positron emission tomography in patients with left clear-cut hippocampal sclerosis. MATERIAL AND METHODS: Twelve right-handed patients who had been operated on left-sided hippocampal sclerosis and 12 right-handed normal subjects were included and the synonym generation task was used for evaluation of language lateralization. RESULTS: Atypical language activations were frequently found in the patients compared to the controls. A total of 3 (25%) subjects in the controls showed atypical activations: 2 bilateral with right and 1 bilateral with left-sided activations. There were no clear right-sided Broca activations in the control group but almost 25% of the patients showed clear right-sided Broca activations. In the patients the incidence of atypical language activations was 91.6% (11 patients). CONCLUSION: From the present study, it is clear that functional reorganization of the language-related neuronal network is modified in patients with left hippocampal sclerosis. Although the lesion is far from the primary language-related areas, atypical language lateralization is common in these patients and this should be considered in preoperative period.
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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) | 0.002 | 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".