Transition to Seizure in the CA3 Hippocampal Network: Predominant Preictal GABAergic Potentials, followed by Predominant Ictal Glutamatergic Potentials
Bibliographic record
Abstract
The mechanisms underlying the transition to seizure are still unresolved. Proposed mechanisms include excitatory GABAergic drive, loss of interneuron-mediated inhibition, and glutamatergic input potentiation. The objective of this thesis was to investigate the relative contributions of synchronized glutamatergic and GABAergic inputs and their functional roles during ictogenesis in the epileptic neonatal (postnatal days 6-12) mouse hippocampus, induced with 0.25mM Mg2+/5mM K+ perfusion. Simultaneous field and whole-cell patch-clamp recordings were obtained from CA3 stratum-oriens interneurons and pyramidal cells. \nThe antagonists for GABAA and glutamate receptors abolished the preictal and ictal discharges, respectively, suggesting that the preictal state is mediated by the coherent discharges of GABAergic inhibitory interneurons, whereas the recurrent excitatory inputs are required for ictogenesis. Synaptic charge transfers underlying the synchronized discharges showed a dynamic change in the balance between the inputs: GABAergic currents markedly diminished by ictal onset whereas glutamatergic currents dominated at ictal onset and throughout the ictus.
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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".