Effect of sleep stage on interictal high‐frequency oscillations recorded from depth macroelectrodes in patients with focal epilepsy
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Bibliographic record
Abstract
PURPOSE: To investigate the effect of sleep stage on the properties of high-frequency oscillations (HFOs) recorded from depth macroelectrodes in patients with focal epilepsy. METHODS: Ten-minute epochs of wakefulness (W), stage 1-2 non-REM (N1-N2), stage 3 non-REM (N3) and REM sleep (R) were identified from stereo-electroencephalography (SEEG) data recorded at 2 kHz in nine patients. Rates of spikes, ripples (>80 Hz), and fast ripples (>250 Hz) were calculated, as were HFO durations, degree of spike-HFO overlap, HFO rates inside and outside of spikes, and inside and outside of the seizure-onset zone (SOZ). RESULTS: Ripples were observed in nine patients and fast ripples in eight. Spike rate was highest in N1-N2 in 5 of 9 patients, and in N3 in 4 of 9 patients, whereas ripple rate was highest in N1-N2 in 4 of 9 patients, in N3 in 4 of 9 patients, and in W in 1 of 9 patients. Fast ripple rate was highest in N1-N2 in 4 of 8 patients, and in N3 in 4 of 8 patients. HFO properties changed significantly with sleep stage, although the absolute effects were small. The difference in HFO rates inside and outside of the SOZ was highly significant (p < 0.000001) in all stages except for R and, for fast ripples, only marginally significant (p = 0.018) in W. CONCLUSIONS: Rates of HFOs recorded from depth macroelectrodes are highest in non-REM sleep. HFO properties were similar in stages N1-N2 and N3, suggesting that accurate sleep staging is not necessary. The spatial specificity of HFO, particularly fast ripples, was affected by sleep stage, suggesting that recordings excluding REM sleep and wakefulness provide a more reliable indicator of the SOZ.
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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 | 0.000 |
| 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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