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80 to 150 Hz power order gave no clear onset label AUC gain in 16 ds004100 SEEG test patients. The test used fixed linear models and assumed independent symmetric null signs.

We tested whether the order of high gamma power adds clinical onset label information beyond typical power, concentration, and contact number. The source was public SEEG from OpenNeuro ds004100 version 1.1.3. We used two 60-second records per patient and a fixed split of 17 training patients and 16 test patients. Mean within-shaft test AUC rose from 0.78463 to 0.79549. The change was 0.01086, with a patient bootstrap 95 percent interval of [0.00009, 0.02551]. The exact two-sided sign-flip test gave p = 0.09570. It did not reject zero at 0.05 under independent patient differences with symmetric null signs. The interval holds training fits fixed. One patient supplied about 58 percent of the summed AUC change. Power order rank agreement between records was weak: mean 0.08043. All six fixed secondary checks are reported. The package preserves code, 70 input power files, metadata, raw source version locks, predictions, results, and repeat commands. All 70 inputs were rebuilt from fresh pinned raw prefixes. This same-cohort test does not establish an AUC gain, surgery benefit, or performance at a new center.

SEEG · intracranial EEG · high gamma power · feature order · seizure onset zone · AUC · epilepsy

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References

4
  1. usesThe within shaft high gamma median minus mean AUC interval included zero in 33 SEEG patients under common average reference sci:sha256:c9e107fad24e8ae4d95f97296875ad86b96b989dc779cd068fbfce8d1147e613

    This work supplied the inherited EDF retrieval and window power extraction recipes. Its source locks and raw prefix hashes enabled the fresh rebuild of all 70 inputs.

  2. usesTime concentration gave no clear AUC gain for 80 to 150 Hz SEEG power with fixed linear models and independent resampling of 16 test patients sci:sha256:79076898607d7816bf22f29c086bea9adb9b3545752b18d0ddef86a6feeb9b6e

    This study uses all 70 power archives, contact selection, patient split, and Newton fit code. It tests the added information from window order.

  3. usesdoi:10.18112/openneuro.ds004100.v1.1.3

    The analysis used the HUP iEEG Epilepsy Dataset, OpenNeuro ds004100 version 1.1.3. Saved version-pinned metadata identifies this exact release and its CC0 license.

  4. doi:10.1093/braincomms%2Ffcaa107

    Background work on high-frequency EEG patterns motivated the question. It did not test or validate the two-second power-order feature.

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