Thalamo-cortical Synchrony Shapes Seizure Expression in Human Temporal Lobe Epilepsy
Bibliographic record
Abstract
Abstract In drug-resistant temporal lobe epilepsy (DR-TLE), electrographic seizures with clinical symptoms (CS) largely determine quality of life, yet some remain silent (NCS) despite arising from the same seizure-onset zone (SOZ). While surgical resection can be curative in select cases, many patients particularly those with bilateral TLE or unresectable networks are not surgical candidates. For these individuals, clarifying why some seizures produce symptoms while others do not is essential for advancing therapy. We hypothesized that thalamo-cortical network engagement may explain this divergence. 286 seizures from 62 DR-TLE patients, included coverage of the pulvinar and/or anterior thalamic group, were analyzed. Thalamo-cortical synchrony, quantified as the correlation between time–frequency patterns in thalamic nuclei and the cortical SOZ, was investigated in relation to seizure type, epilepsy subtype, thalamic region, and one-year post-resection surgical outcome. Thalamo-cortical synchrony was stronger during CS than NCS (p < 0.0001, δ > 0.6), regardless of epilepsy subtype, thalamic region, seizure subtype, or outcome, and confirmed within patients. Multivariate analysis identified seizure type as the only independent predictor (p < 0.001). These findings establish thalamo-cortical synchrony as a network-level marker of clinical seizure expression and highlight the potential of neuromodulation to modulate seizure expression when resection is not feasible.
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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 | 0.000 |
| 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) | 0.002 | 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".