GABAA signaling, focal epileptiform synchronization and epileptogenesis
Bibliographic record
Abstract
Under physiological conditions, neuronal network synchronization leads to different oscillatory EEG patterns that are associated with specific behavioral and cognitive functions. Excessive synchronization can, however, lead to focal or generalized epileptiform activities. It is indeed well established that in both epileptic patients and animal models, focal epileptiform EEG patterns are characterized by interictal and ictal (seizure) discharges. Over the last three decades, employing in vitro and in vivo recording techniques, several experimental studies have firmly identified a paradoxical role of GABAA signaling in generating interictal discharges, and in initiating—and perhaps sustaining—focal seizures. Here, we will review these experiments and we will extend our appraisal to evidence suggesting that GABAA signaling may also contribute to epileptogenesis, i.e., the development of plastic changes in brain excitability that leads to the chronic epileptic condition. Overall, we anticipate that this information should provide the rationale for developing new specific pharmacological treatments for patients presenting with focal epileptic disorders such as mesial temporal lobe epilepsy (MTLE).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".