High and Low-Frequency Stimulation Effect on Epileptiform Activity in Brain Slices
Bibliographic record
Abstract
Background: Neurostimulation is one of the new therapeutic approaches in patients with drug-resistant epilepsy, and despite its high efficiency, its mechanism of action is still unclear. On the one hand, electrical stimulation in the human brain is immoral; on the other hand, the creation of the epilepsy model in laboratory animals affects the entire brain network. As a result, one of the ways to achieve the neurostimulation mechanism is to use epileptiform activity models In vitro. In vitro models, by accessing the local network from the whole brain, we can understand the mechanisms of action of neurostimulation. Methods: A literature search using scientific databases including PubMed, Google Scholar, and Scopus, using "Neurostimulation" and "epileptiform activity" combined with "high-frequency stimulation", " low-frequency stimulation ", and "brain slices" as keywords were conducted, related concepts to the topic gathered and are used in this paper. Results: Electrical stimulation causes neuronal depolarization and the release of GABAA, which inhibits neuronal firing. Also, electrical stimulation inhibits the nervous tissue downstream of the stimulation site by preventing the passage of nervous activity from the upstream to the downstream of the axon. Conclusion: Neurostimulation techniques consisting of LFS and HFS have a potential role in treating epileptiform activity, with some studies having positive results. Further investigations with larger sample sizes and standardized outcome measures can be conducted to validate the results of previous studies.
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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 | 0.001 | 0.002 |
| 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".