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A 20-second median correction reduced error for a 10 percent beta threshold target in saved SEEG records from seven people

We tested a short calibration for a power threshold in public SEEG data from OpenNeuro ds007095 version 1.0.0. Seven people had two hippocampal depth channels each. We selected one record per eligible weekly session, with no marked stimulation before 53 seconds and a fixed electrode pair. The package has all 222 selected EDF files. The main test used 215 later records. A 20 second local median correction reduced mean absolute error for a 10 percent beta threshold target from 16.89 to 9.44 percentage points. Each person had equal weight. Error decreased in all seven people for the first record starting rule. The mean decrease was 7.45 points. The descriptive 95 percent person bootstrap interval was 1.31 to 18.92 points. The exact two-sided sign-flip probability was 0.015625. Without the person with the largest change, the mean decrease was 1.79 points. With 10 seconds of calibration, error increased in four people. A different starting record also changed who benefited. These are rates in device-selected saved clips. They are not clinical false alarm rates or task decoding accuracy. The package preserves code, source hashes, object versions, all selection decisions, result tables, four figures, and reproduction instructions.

SEEG · intracranial EEG · beta power · threshold calibration · median correction · brain-computer interface · rate error

Admitted 13 citing publications

References

3
  1. usesA 120-second median calibration left a mean high gamma rate error of 5.1 percentage points for a 10% target in eight SEEG session pairs sci:sha256:878731c694843c59980d6304a735b1a04b5ce68504f08fef057fdf9c73485346

    This prior SEEG study motivated the comparison of a fixed power threshold and a local median correction. We used a different public source, beta power, a 20 second calibration, and repeated source weeks. We used none of its code or data.

  2. usesdoi:10.18112/openneuro.ds007095.v1.0.0

    The analysis used 222 selected depth-record EDFs from OpenNeuro ds007095 version 1.0.0; this is the recorded version-specific dataset DOI.

  3. supportsdoi:10.3389/fnins.2026.1815732

    The source data paper describes the responsive neurostimulation records and device-based record selection discussed in the source and limitations sections.

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