Thalamocortical dysrhythmia in intraoperative recordings of focal epilepsy
Bibliographic record
Abstract
Resonant interactions between the thalamus and cortex subserve a critical role for maintenance of consciousness as well as cognitive functions. In states of abnormal thalamic inhibition, thalamocortical dysrhythmia (TCD) has been described. The characteristics of TCD include a slowing of resting oscillations, ectopic high-frequency activity, and increased cross-frequency coupling. Here, we demonstrate the presence of TCD in four patients who underwent resective epilepsy surgery with chronically implanted electrodes under anesthesia, continuously recording activity from brain regions at the periphery of the epileptogenic zone before and after resection. Following resection, we report an acceleration of the large-scale network resting frequency coincident with decreases in cross-frequency phase-amplitude coupling. Interregional functional connectivity in the surrounding cortex was also increased following resection of the epileptogenic focus. These findings provide evidence for the presence of TCD in focal epilepsy and highlight the importance of reciprocal thalamocortical oscillatory interactions in defining novel biomarkers for resective surgeries. NEW & NOTEWORTHY Thalamocortical dysrhythmia (TCD) occurs in the context of thalamic dysfacilitation and is characterized by slowing of resting oscillations, ectopic high-frequency activity, and cross-frequency coupling. We provide evidence for TCD in focal epilepsy by studying electrophysiological changes occurring at the periphery of the resection margin. We report acceleration of resting activity coincident with decreased cross-frequency coupling and increased functional connectivity. The study of TCD in epilepsy has implications as a biomarker and therapeutic target.
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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 | 0.000 | 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) | 0.001 | 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".