Neurosteroids differentially modulate fast and slow interictal discharges in the hippocampal<scp>CA</scp>3 area
Bibliographic record
Abstract
Two types of spontaneous interictal discharge, identified as fast and slow events, can be recorded from the hippocampal CA3 area in rat brain slices during application of 4-aminopyridine (4AP) (50 μm). Here, we addressed how neurosteroids modulate the occurrence of these interictal events and of the associated high-frequency oscillations (HFOs) (ripples, 80-200 Hz; fast ripples, 250-500 Hz). Under control conditions (i.e. during 4AP application), ripples and fast ripples were detected in 12.3 and 17.5% of fast events, respectively; in contrast, the majority of slow events (> 98%) did not co-occur with HFOs. Application of 0.1, 1 or 5 μm allotetrahydrodeoxycorticosterone (THDOC) to 4AP-treated slices caused a dose-dependent decrease in the duration of the fast events and an increase in the occurrence of ripples, but not fast ripples; in contrast, the duration of slow events increased. THDOC potentiated the slow events that were recorded during pharmacological blockade of glutamatergic transmission, but had no effect on interictal discharges occurring during GABAA receptor antagonism. These results demonstrate that potentiation of GABAA receptor-mediated signaling by THDOC differentially affects slow and fast interictal discharges; these differences may provide insights into how hyperexcitable activity is influenced by neurosteroids.
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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 | 0.001 |
| 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".