Correlations between Limbic White Matter and Cognitive Function in Temporal-Lobe Epilepsy, Preliminary Findings
Bibliographic record
Abstract
The limbic system is presumed to have a central role in cognitive performance, in particular memory. The purpose of this study was to investigate the relationship between limbic white matter microstructure and neuropsychological function in temporal-lobe epilepsy (TLE) patients using diffusion tensor imaging (DTI). Twenty-one adult TLE patients, including 7 non-lesional (nlTLE) and 14 with unilateral mesial temporal sclerosis (uTLE), were studied with both DTI and hippocampal T2 relaxometry. Correlations were performed between fractional anisotropy (FA) of the bilateral fornix and cingulum, hippocampal T2, neuropsychological tests. Positive correlations were observed in the whole group for the left fornix and processing speed index. In contrast, memory tests did not show significant correlations with DTI findings. Subgroup analysis demonstrated an association between the left fornix and processing speed in nlTLE but not uTLE. No correlations were observed between hippocampal T2 and test scores in either the TLE group as a whole or after subgroup analysis. Our findings suggest that integrity of the left fornix specifically is an important anatomical correlate of cognitive function in TLE patients, in particular patients with nlTLE.
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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 | 0.001 | 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) | 0.001 | 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".