Preoperative simulation of intracerebral epileptiform discharges: synthetic aperture magnetometry virtual sensor analysis of interictal magnetoencephalography data
Bibliographic record
Abstract
OBJECT: Magnetoencephalography (MEG) has been used for the preoperative localization of epileptic equivalent current dipoles (ECDs) in neocortical epilepsy. Spatial filtering can be applied to MEG data by means of synthetic aperture magnetometry (SAM), and SAM virtual sensor analysis can be used to estimate the strength and temporal course of the epileptic source in the region of interest. To evaluate the clinical usefulness of this approach, the authors compare the results of SAM virtual sensor analysis to the results of ECD analysis, subdural electroencephalography (EEG) findings, and surgical outcomes in pediatric patients with neocortical epilepsy. METHODS: Ten pediatric patients underwent MEG, invasive subdural EEG, and cortical resection for neocortical epilepsy. The authors compared the morphological characteristics, quantity, location, and distribution of the epileptiform discharges assessed using SAM and ECD analysis, and subdural EEG findings (interictal discharges and ictal onset zones). In nine patients, MEG revealed clustered ECDs. The region exhibiting the maximum percentage (> or = 70%) of spikes/sharp waves on SAM was colocalized to clustered ECDs in seven patients. In six patients, SAM demonstrated focal spikes; in two, diffuse spikes; and in two others, focal rhythmic sharp waves. These epileptiform discharges were similar to those recorded on subdural EEG. In nine patients, concordant regions containing the maximum percentage of spikes/sharp waves were revealed by SAM and subdural EEG data. The region of the maximum percentage of spikes/sharp waves as demonstrated by SAM was colocalized to the ictal onset zone identified by subdural EEG findings in seven patients and partially colocalized in two. CONCLUSIONS: The SAM virtual sensor analysis revealed morphological characteristics, location, and distribution of epileptiform discharges similar to those shown by subdural EEG recordings. By using SAM it is possible to predict intracerebral interictal epileptiform discharges in the region of interest from noninvasively collected preoperative MEG data. The maximum interictal discharge zone identified by SAM virtual sensors correlated to clustered ECDs and the ictal onset zone on subdural EEG findings. Complementary analyses of ECDs and SAM on three-dimensional MR images can improve delineation of epileptogenic zones and lesions in neocortical epilepsy.
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 | 0.002 |
| 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".