Two Seizure-Onset Types Reveal Specific Patterns of High-Frequency Oscillations in a Model of Temporal Lobe Epilepsy
Bibliographic record
Abstract
High-frequency oscillations (HFOs; 80-500 Hz) are thought to mirror the pathophysiological changes occurring in epileptic brains. However, the distribution of HFOs during seizures remains undefined. Here, we recorded from the hippocampal CA3 subfield, subiculum, entorhinal cortex, and dentate gyrus to quantify the occurrence of ripples (80-200 Hz) and fast ripples (250-500 Hz) during low-voltage fast-onset (LVF) and hypersynchronous-onset (HYP) seizures in the rat pilocarpine model of temporal lobe epilepsy. We discovered in LVF seizures that (1) progression from preictal to ictal activity was characterized in seizure-onset zones by an increase of ripple rates that were higher when compared with fast ripple rates and (2) ripple rates during the ictal period were higher compared with fast ripple rates in seizure-onset zones and later in regions of secondary spread. In contrast, we found in HYP seizures that (1) fast ripple rates increased during the preictal period and were higher compared with ripple rates in both seizure-onset zones and in regions of secondary spread and (2) they were still higher compared with ripple rates in both seizure-onset zones and regions of secondary spread during the ictal period. Our findings demonstrate that ripples and fast ripples show distinct time- and region-specific patterns during LVF and HYP seizures, thus suggesting that they play specific roles in ictogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".