Blockade of in vitro ictogenesis by low-frequency stimulation coincides with increased epileptiform response latency
Bibliographic record
Abstract
Low-frequency stimulation, delivered through transcranial magnetic or deep-brain electrical procedures, reduces seizures in patients with pharmacoresistant epilepsy. A similar control of ictallike discharges is exerted by low-frequency electrical stimulation in rodent brain slices maintained in vitro during convulsant treatment. By employing field and "sharp" intracellular recordings, we analyzed here the effects of stimuli delivered at 0.1 or 1 Hz in the lateral nucleus of the amygdala on ictallike epileptiform discharges induced by the K(+) channel blocker 4-aminopyridine in the perirhinal cortex, in a rat brain slice preparation. We found that 1) ictal events were nominally abolished when the stimulus rate was brought from 0.1 to 1 Hz; 2) this effect was associated with an increased latency of the epileptiform responses recorded in perirhinal cortex following each stimulus; and 3) both changes recovered to control values following arrest of the 1-Hz stimulation protocol. The control of ictal activity by 1-Hz stimulation and the concomitant latency increase were significantly reduced by GABAB receptor antagonism. We propose that this frequency-dependent increase in latency represents a short-lasting, GABAB receptor-dependent adaptive mechanism that contributes to decrease epileptiform synchronization, thus blocking seizures in epileptic patients and animal models.
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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) | 0.001 | 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".