American Clinical Neurophysiology Society Technical Standards for Performing Intraoperative Electrocorticography
Bibliographic record
Abstract
PURPOSE: These consensus guidelines by the American Clinical Neurophysiology Society (ACNS) describe best practices for performing intraoperative Electrocorticography (ioECoG) using subdural or depth electrodes for adult and pediatric population. METHODS: A group of ACNS members was convened to develop technical standards for performing ioECoG. PubMed searches were performed to identify pertinent peer-reviewed literature. Sections were assigned to individual authors based on expertise. Consensus was achieved during subsequent group discussions to develop evidence-based recommendations to the extent possible. RECOMMENDATIONS: Communication between the neurosurgical and the neurophysiology teams is essential in verifying and documenting the location of the contacts. Most authors recommend ioECoG recordings of at least 5 and up to 30 minutes in duration to allow for sufficient observation of interictal activity. The anesthesia should be adjusted to allow continuous EEG activity and to minimize the effect on the ioECoG recording during general anesthesia or awake surgery. The surgical procedure and technical report should separate ioECoG recordings to define the irritative zone from ioECoG findings during functional mapping. The neurophysiology physician's physical presence in the operating room is required in the definition of the services. CONCLUSION: These consensus guidelines by the ACNS describe best practices for performing intraoperative ECoG based on published literature and expert consensus.
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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 | 0.084 | 0.170 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.011 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".