Removing Eye‐movement Artifacts from the EEG during the Intracarotid Amobarbital Procedure
Bibliographic record
Abstract
PURPOSE: The EEG is often recorded during the intracarotid amobarbital procedure (IAP) to help in the assessment of the spatial extent and the duration of the effect of the drug. In scalp recordings, the EEG is always heavily contaminated with eye movement artifacts as the patient actively performs visual tasks. METHODS: Independent component analysis (ICA) is a new technique for blind source separation. In this study, we separated the EEG data recorded during the IAP into independent components using ICA. The EEG signal was reconstructed by excluding the components related to eye movement and eye blinks. RESULTS: EEGs from 10 IAP tests were analyzed. The experimental results indicate that ICA is very efficient at subtracting eye-movement artifacts, while retaining the EEG slow waves and making their interpretation easier. CONCLUSIONS: ICA appears to be a generally applicable and effective method for removing ocular artifacts from EEG recordings during IAP, although slow waves and ocular artifacts share similar frequency distributions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".