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Selection of trials present in every channel kept 315 of 719 observed trials in seven recordings marked as SEEG

We tested channel availability and complete object recall in six patients with epilepsy. We used seven processed recordings from OpenNeuro ds006136 version 1.0.1. Source JSON files mark all 58 channels as SEEG. Channel tables use EEG. The adjusted mean availability difference was -1.37 percentage points. Its 95 percent t interval was -9.57 to +6.83 points. The exact patient sign-flip test gave p = 0.65625. It requires independent patients and symmetric signs under the null. The test did not detect a mean association. It does not establish equal availability. A rule that required every trial in every channel kept 315 of 719 observed trials, or 43.81 percent. Among 46 eligible channels from four patients, the mean absolute change in the late-delay high-gamma recall coefficient was 0.207 dB. This was a descriptive sample check. The package contains inclusion tables, power features, code, fixed source versions, results, and repeat instructions. All seven source signal hashes matched. Separate calculations and a fresh source-data run reproduced the numerical results. Trials absent from every channel have unknown recall.

trial availability · trial selection · object working memory · intracranial EEG · high-gamma power · reproducibility

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References

3
  1. usesRow joins paired different trial IDs in most frontal and temporal comparisons in public SEEG from five patients sci:sha256:61b7eb6e8b7d8639f1da6682e68131f4e06a45c86631e52bd3aa14e5b4476687

    This study used fixed source retrieval pins and three unchanged code files from the earlier audit. They enabled a fresh extraction from all seven Missouri EDF files. The old feature table was used only to check the new features. The same patients are used.

  2. usesdoi:10.18112/openneuro.ds006136.v1.0.1

    This analysis uses the seven processed recordings in OpenNeuro ds006136 version 1.0.1; the saved metadata identify this exact release and its CC0 license.

  3. doi:10.1016/j.neuroimage.2026.121718

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