Bibliographic record
Abstract
Electrical kindling, repeated brain stimulation eventually resulting in seizures, is widely used as an animal model of epileptogenesis and epilepsy. However, the stimulation electrode used for electric kindling targets unknown neuronal populations and may introduce tissue damage and inflammation. Optogenetics can be used to circumvent these shortcomings by permitting millisecond control of activity in genetically defined neurons without gross injury or inflammation. Here we describe an easy step-by-step protocol for optogenetic kindling - optokindling - by which seizures are eventually elicited in initially healthy mice through repeated light stimulation of neurons expressing Channelrhodopsin-2 (ChR2). Chronic EEG recordings may be performed over large time scales to monitor activity while video camera monitoring may be used to assess the behavioral severity of seizures. In conclusion, with optokindling, neuroscientists can elucidate the circuit changes that underpin epilepsy while minimizing the contribution of confounding factors such as brain damage and inflammation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".