Electrical stimulation-induced correlates of epileptogenicity in a non-human primate model of mesial temporal lobe epilepsy
Bibliographic record
Abstract
Mesial temporal lobe epilepsy (mTLE) is a widespread focal seizure disorder, with approximately one-third of patients left untreated by anti-seizure medications (refractory epilepsy) (Kwan and Brodie, 2000). A potential avenue for improving the outcome of surgery and seizure control in refractory epilepsy patients is analyzing changes in electrophysiology throughout the development of epilepsy. In animals, repeatedly stimulating the amygdala (kindling) results in epileptogenic models and produces afterdischarges (ADs) (Goddard et al., 1969). ADs mimic clinical seizure electrophysiology and can potentially be used as a biomarker of tissue epileptogenicity. This study establishes an electrically kindled non-human primate (NHP) model of chronic mTLE with clinical seizure semiology. Epileptogenesis is observed in two NHPs, with significant changes in AD length observed in both primates over months of repeated kindling. Further, reductions in the AD threshold are observed after a seventy-seven-week cessation of kindling, indicating chronicity of kindling-induced changes. The model is further validated by investigating changes in field-evoked potentials recorded throughout kindling using microstimulation, which indicates sensitization of temporal lobe networks to kindling stimulation. Further research in this model has the potential to uncover a method for correlating evoked potential responses to the degree of epileptic activity in primate neural tissue. Future studies should aim to identify similar electrophysiologic findings in human epilepsy patients to refine the neural mapping process of human epilepsy surgery.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".