P.035 Correlation of thalamic connectivity with the duration of epilepsy in patients with temporal lobe epilepsy
Bibliographic record
Abstract
Background: Morphometry and connectivity studies targeting the thalamus have revealed specific patterns of atrophy and deafferentiation in patients with temporal lobe epilepsy (TLE). We used probabilistic tractography to investigate thalamic connectivity with respect to duration of epilepsy and surgical outcomes in TLE. Methods: Patients (N=20) with drug-resistant TLE (10 short duration (<15 years), 10 long duration (>15 years)) were scanned with multi-parametric 3T MRI and compared with 34 healthy controls. The Harvard-Oxford atlas was modified to create 14 target regions in the temporal lobes. Probabilistic tractography (FSL) was used to delineate thalamic sub-regions most connected to each target. The volume, mean T1, T2, FA and MD of each thalamic sub-region was quantified. Surgical success was quantified using Engel outcome scores. Results: Significant decreases in thalamic connected volumes to the hippocampus in patients with longer duration of TLE were revealed. Likewise, when stratified based on surgical success, significant differences in diffusion metrics to the hippocampus, parahippocampal gyrus, and temporal neocortex were found. Significant differences did not withstand false discovery rate (FDR) correction. Conclusions: These findings suggest ongoing connectivity changes dependent on epilepsy duration and promote further investigation into the use of thalamic connectivity data as biomarkers for predicting surgical outcomes in TLE patients.
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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 | 0.000 | 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) | 0.006 | 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".