Concordance rate between Wada and fMRI tests for visual memory assessment of patients with medically intractable temporal lobe epilepsy
Bibliographic record
Abstract
Background: There is not enough evidence to prove either invasive Wada or non-invasive fMRI test predicts postoperative memory changes more accurately in patients with refractory temporal lobe epilepsy (TLE). In this study, concordance between fMRI and Wada test for postoperative assessment of visual memory is investigated. Methods: fMRI test with a novel scene-encoding task were conducted on our cohort of patients. fMRI laterality indices (LI) were then defined as a ratio (L-R)/(L+R) between the number of activated voxels in the left and right of two regions: hippocampus+parahippocampus (Region A) and temporal lobe - (hippocampus+parahippocampus) (Region B). fMRI results were divided into the right (LI < -0.2), left (LI > 0.2) or bilateral (-0.2 < LI <0.2) hemispheric memory dominance and compared to the results of the Wada test. Results: 19 patients were studied (14 left TLE, 3 right TLE and 2 bilateral TLE). The concordance rate between Wada and fMRI tests was 36.8% and 42.1% for regions A and B. Conclusions: Based on the results, the concordance rate between the Wada test and the fMRI test is not high. As a future work, we will investigate the correlation of each test to postoperative memory outcome.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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; 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".