A method for actively tracking excitability of brain networks using a fully implantable monitoring system
Bibliographic record
Abstract
This paper introduces a new method for estimating the excitability of brain networks. The motivation for this research was to develop a system that can track pathological changes in excitability, in diseases such as epilepsy. The ability to track excitability may provide a method for anticipating seizures and intervening therapeutically. Four normally healthy canines were implanted with the Medtronic Activia PC+S deep brain stimulation and sensing system. The devices were used to probe the circuit of Papez, with electrical stimulation in the anterior nucleus of the thalamus to measure evoked potentials in the hippocampus. The canines were given three different dosage levels of anti-convulsant medication in an attempt to manipulate the excitability of the network. The results showed changes in the morphology of the evoked potentials, following a circadian profile and reflecting times of drug delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".