Superficial and deep white matter abnormalities in temporal lobe epilepsy
Bibliographic record
Abstract
Abstract Non-invasive neuroimaging is important in epilepsy to help identify cerebral abnormalities. Abnormally reduced fractional anisotropy (FA) in deep white matter (WM) from diffusion-weighted imaging (DWI) is widely reported in large multi-cohort studies across all types of epilepsies. However, abnormalities in FA for superficial WM are rarely investigated in epilepsy. To gain a greater understanding of the nature of WM abnormality at different WM depths, we investigated DWI abnormalities at a range of superficial and deep WM in two separate temporal lobe epilepsy (TLE) cohorts. The first cohort (TLE = 81, Healthy Control; HC = 67) underwent a high angular resolution multi-shell DWI, whilst the second cohort (TLE = 70, HC = 29) had a single-shell acquisition. We registered FA maps to a standard template, and analysed temporal WM within 8 mm of the temporal lobe grey matter, amygdala and hippocampus. We standardised FA measures at different depths, and compared ipsi-versus contralateral temporal WM, and MRI-positive versus MRI-negative groups. We report three major findings: First, superficial WM had greater FA reductions than deep WM in TLE (P < 0.001). Second, this effect was more prominent in the ipsilateral than contralateral temporal lobe WM (P < 0.001). Third, these effects were present to a similar degree in patients who reported an MRI negative. All results are held in both TLE cohorts. These findings suggest that, in the temporal lobe, superficial WM is more abnormal than deep WM in TLE, with potential clinical use for lateralisation even in MRI-negative patients. These findings motivate further investigation of the importance of superficial WM in epilepsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".