Electroencephalographic Dipoles of Spikes With and Without Myoclonic Jerks Caused by Epilepsia Partialis Continua
Bibliographic record
Abstract
We used electroencephalographic (EEG) dipole analysis to investigate the generators of spikes with and without myoclonic jerks in a 12-year-old patient with epilepsia partialis continua secondary to left parietal cortical dysplasia. We recorded EEG and right wrist extensor electromyography (EMG) and collected 42 spikes with jerks (jerking spikes) and 42 spikes without jerks (nonjerking spikes). We applied a single moving dipole model to the individual and averaged spikes. Dipoles at the negative peak of individual jerking and nonjerking spikes were localized in the dysplastic area. At the onset of the averaged jerking spike that preceded the EMG discharges by 20 ms, the dipole was in the motor cortex, whereas for the averaged nonjerking spike, the dipole was in the sensory cortex. The dipole moment at averaged jerking spike onset was twice that of the averaged nonjerking spike. Electroencephalographic dipole analysis of averaged spikes differentiated the generator of jerking and nonjerking spikes in epilepsia partialis continua. Individual dipoles demonstrated the area of epileptogenic cortical dysplasia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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 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".