Source Imaging of Triphasic Waves and Other Encephalopathies
Bibliographic record
Abstract
PURPOSE: Triphasic waves (TWs) are defined as high-amplitude positive waveforms with preceding and after-going negative waves, typically seen in medically ill patients. TWs manifest in similar clinical presentations as other EEG encephalopathies; however, electrographically, they appear different. To better understand the difference, the authors used two different source localization software programs to find a reproducible and unique signature for TW. METHODS: EEGs performed at Johns Hopkins Hospital and Duke University Hospital were retrospectively analyzed. EEG samples of TW, Delta, Theta-Delta, and Frontal Intermittent Rhythmic Delta Activity were selected. The authors did source localization via Commercial Curry 8 and open-source Brainstorm software. A minimum of 10 stereotypical waveforms per subject were selected. The authors used the Boundary Element Method for the head model, which was derived from the Montreal Neurological Institute averaged imaging data set. Dipole and current density analyses were performed. RESULTS: Twenty-eight patients were selected (10 TW, 4 Frontal Intermittent Rhythmic Delta Activity, 6 Theta-Delta, and 8 Delta). The findings suggest the activation of anterior frontal and midline structures for TW. Frontal Intermittent Rhythmic Delta Activity had a similar localization but without a moving dipole. In comparison, the Delta and Delta-Theta appeared to have a more diffuse origin. CONCLUSIONS: Source analysis of TW via two different software suggests the anterior midline location of TW with anterior to posterior propagation. These findings correlate with the previous hypotheses of TW origin. Retrospective analysis, low number of recording electrodes, and difficult analysis of slow waves limit the interpretation of these results. Nonetheless, this article opens the prospect of future studies in this field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".