Activation of specific neuronal networks leads to different seizure onset types
Bibliographic record
Abstract
OBJECTIVE: Ictal events occurring in temporal lobe epilepsy patients and in experimental models mimicking this neurological disorder can be classified, based on their onset pattern, into low-voltage, fast versus hypersynchronous onset seizures. It has been suggested that the low-voltage, fast onset pattern is mainly contributed by interneuronal (γ-aminobutyric acidergic) signaling, whereas the hypersynchronous onset involves the activation of principal (glutamatergic) cells. METHODS: Here, we tested this hypothesis using the optogenetic control of parvalbumin-positive or somatostatin-positive interneurons and of calmodulin-dependent, protein kinase-positive, principal cells in the mouse entorhinal cortex in the in vitro 4-aminopyridine model of epileptiform synchronization. RESULTS: We found that during 4-aminopyridine application, both spontaneous seizure-like events and those induced by optogenetic activation of interneurons displayed low-voltage, fast onset patterns that were associated with a higher occurrence of ripples than of fast ripples. In contrast, seizures induced by the optogenetic activation of principal cells had a hypersynchronous onset pattern with fast ripple rates that were higher than those of ripples. INTERPRETATION: Our results firmly establish that under a similar experimental condition (ie, bath application of 4-aminopyridine), the initiation of low-voltage, fast and of hypersynchronous onset seizures in the entorhinal cortex depends on the preponderant involvement of interneuronal and principal cell networks, respectively.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".