Modelling Hyperexcitability in Human Cerebral Organoids: A Platform for Epilepsy Drug Testing
Bibliographic record
Abstract
Epilepsy is a complex neurological condition characterized by recurrent seizures, that affects 1% of the population. A third of people with epilepsy do not respond to drugs and there is not one drug that treats all; thus, better models of epilepsy are needed for drug development. Human cerebral organoids resemble the 3D complexity of the human brain and have the potential to augment current drug development pipelines. In the present work, human cerebral organoids are used along with electrophysiological methods to explore various means of inducing seizures. The resulting activity is characterized through signal processing and manual event analysis. Furthermore, this hyperexcitable activity is investigated in its response to current anti-seizure drugs. These findings demonstrate the presence of hyperexcitable changes in the cerebral organoid tissue, which supports the use of organoids as a platform for modelling epilepsy, as well as provides a framework for testing anti-seizure drug efficacy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".