Faculty Opinions recommendation of A disinhibitory nigra-parafascicular pathway amplifies seizure in temporal lobe epilepsy.
Bibliographic record
Abstract
The precise circuit of the substantia nigra pars reticulata (SNr) involved in temporal lobe epilepsy (TLE) is still unclear.Here we found that optogenetic or chemogenetic activation of SNr parvalbumin + (PV) GABAergic neurons amplifies seizure activities in kindling-and kainic acid-induced TLE models, whereas selective inhibition of these neurons alleviates seizure activities.The severity of seizures is bidirectionally regulated by optogenetic manipulation of SNr PV fibers projecting to the parafascicular nucleus (PF).Electrophysiology combined with rabies virus-assisted circuit mapping shows that SNr PV neurons directly project to and functionally inhibit posterior PF GABAergic neurons.Activity of these neurons also regulates seizure activity.Collectively, our results reveal that a long-range SNr-PF disinhibitory circuit participates in regulating seizure in TLE and inactivation of this circuit can alleviate severity of epileptic seizures.These findings provide a better understanding of pathological changes from a circuit perspective and suggest a possibility to precisely control epilepsy.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.047 |
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".