Methodologic recommendations and possible interpretations of video‐<scp>EEG</scp> recordings in immature rodents used as experimental controls: A TASK1‐WG2 report of the ILAE/AES Joint Translational Task Force
Bibliographic record
Abstract
The use of immature rodents to study physiologic aspects of cortical development requires high-quality recordings electroencephalography (EEG) with simultaneous video recording (vEEG) of behavior. Normative developmental vEEG data in control animals are fundamental for the study of abnormal background activity in animal models of seizures or other neurologic disorders. Electrical recordings from immature, freely behaving rodents can be particularly difficult because of the small size of immature rodents, their thin and soft skull, interference with the recording apparatus by the dam, and other technical challenges. In this report of the TASK1 Working Group 2 (WG2) of the International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force, we provide suggestions that aim to optimize future vEEG recordings from immature rodents, as well as their interpretation. We focus on recordings from immature rodents younger than 30 days old used as experimental controls, because the quality and correct interpretation of such recordings is important when interpreting the vEEG results of animals serving as models of neurologic disorders. We discuss the technical aspects of such recordings and compare tethered versus wireless approaches. We also summarize the appearance of common artifacts and various patterns of electrical activity seen in young rodents used as controls as a function of behavioral state, age, and (where known) sex and strain. The information herein will hopefully help improve the methodology of vEEG recordings from immature rodents and may lead to results and interpretations that are more consistent across studies from different laboratories.
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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 | 0.068 | 0.063 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".