High-frequency cortical activity associated with postischemic epileptiform discharges in an in vivo rat focal stroke model
Bibliographic record
Abstract
OBJECT: The postischemic brain has greater susceptibility to epileptogenic activity than physiologically healthy tissue. Epileptiform discharges are thought to exacerbate postischemic brain function. The aim of this study was to develop an in vivo focal stroke model in rats to characterize epileptiform activity. METHODS: The authors developed a parasagittal 8-channel intracortical microelectrode array to obtain recordings of cortical oscillations of local field potentials following partial middle and anterior cerebral artery occlusion. All experiments were done in urethane-anesthetized Sprague-Dawley rats. RESULTS: Theta runs (TRs), ranging in duration from 5 seconds to 5 minutes, were observed in 62% of animals within 1 hour of occlusion. High-frequency oscillations (HFOs) in the high gamma range (80-120 Hz) were observed 5-15 seconds before each TR and terminated at the onset of the discharge. Periodic epileptiform discharges (PEDs) were detected in 54% of rats following ischemia. The PEDs consisted of an early negative slow wave, a high-amplitude positive spike, and a short negative slow wave. Transient HFOs in the low gamma range (30-70 Hz) occurred during the first negative wave and the rising phase of the positive spike of the PED. CONCLUSIONS: These recordings provide the first intracortical evidence of a high-frequency component that could be an important element for diagnosis and intervention in postischemic epileptogenic activity. The early onset also suggests that HFOs could serve as a reliable method of detecting small epileptiform events and could be used as a consideration in deciding whether antiepileptic medications are appropriate as part of a patient's poststroke care.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".