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Record W2018816470 · doi:10.3171/jns.2001.94.6.1005

Computerized brain-surface voltage topographic mapping for localization of intracranial spikes from electrocorticography

2001· article· en· W2018816470 on OpenAlexaff
Hiroshi Otsubo, Atsushi Shirasawa, Shiro Chitoku, James T. Rutka, Scott B. Wilson, O. Carter Snead

Bibliographic record

VenueJournal of neurosurgery · 2001
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsIctalElectrocorticographyEpilepsy surgeryMedicineStereoelectroencephalographyElectroencephalographyEpilepsyBiomedical engineering

Abstract

fetched live from OpenAlex

The purpose of this paper is to describe the use of computerized brain-surface voltage topographic mapping to localize and identify epileptic discharges recorded on electrocorticographic (ECoG) studies in which a subdural grid was used during intracranial video electroencephalographic (IVEEG) monitoring. The authors studied 12 children who underwent surgery for intractable extrahippocampal epilepsy. Cortical surfaces and subdural grid electrodes were photographed during the initial surgery to create an electrode map that could be superimposed onto a picture of the brain surface. Spikes were selected from ictal discharges recorded at the beginning of clinically confirmed seizures and from interictal discharges seen on ECoG studies during IVEEG recording. A computer program was used to calculate the sequential amplitude of the spikes by using squared interpolation, and they were then superimposed onto the electrode map. Interictal discharges and high-amplitude spike complexes at seizure onset were plotted on the map. This mapping procedure depicted the ictal zone in nine patients and the interictal zone in 12, and proved to be an accurate and useful source of information for planning corrective surgery.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.259
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2001
Admission routes1
Has abstractyes

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