Role of Functional MRI in Presurgical Evaluation of Memory Function in Temporal Lobe Epilepsy
Bibliographic record
Abstract
Many diagnostic tools have been employed to predict the likelihood of a postoperative memory decline after a standard temporal lobectomy, including the intracarotid amobarbital testing (IAT) or Wada, regarded as the gold standard test for over the past half a century. Functional MRI (fMRI) is also a promising tool in that regard. Its routine use to predict the postoperative memory decline has been limited because of the varied study paradigms, discrepancies in analysis, and interpretation of the results. Based on the existing literatures, fMRI cannot replace IAT for the routine presurgical evaluation of the patients with temporal lobe epilepsy (TLE) yet. Large multicentre studies with a panel of memory test are required to determine the full potential of fMRI and use it reliably to replace IAT in the routine clinical practice. In this paper, we review various aspects of memory fMRI, including the experimental designs, data analysis, and findings.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".