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Fixed gates for low power at 70 to below 110 Hz preceded a mean 2.94 dB rise without task stimulation in nine SEEG rest recordings

We tested a control for brain interfaces that use measured power to choose stimulation times. Nine public SEEG rest recordings supplied 539 bipolar pairs. Each record had 352 separate 0.5 s windows. We fixed each pair's low-power gate at the early 20th percentile in the 70 to below 110 Hz band. At later gate times, the next window rose by 2.94 dB on average. The 95% person bootstrap interval was 2.30 to 3.80 dB. The contrast with all candidate times was 2.95 dB, with an interval of 2.32 to 3.81 dB. All nine person contrasts were positive. No task stimulation was applied. High-power gates were followed by a mean change of -3.15 dB. The low-gate contrast stayed positive with longer gates, delayed outcomes, a refractory rule, and one pair per shaft. The result is a no-stimulation control benchmark for a known selection problem. A rise from a selected low value does not establish a stimulation response. The data do not separate neural changes from measurement noise or artifacts. The package includes features, source metadata, fresh raw audit samples, full source hash checks, code, tables, and three figures.

SEEG · intracranial EEG · power gate · regression to the mean · brain interfaces · no-stimulation control · rest recordings

Admitted 2 citing publications

References

5
  1. usesA passive speech detector exceeded 5% activation in three of nine SEEG rest recordings after music calibration sci:sha256:3caf09d075a0074a3fdb0cdc0b8e28e9759a39af46c06696e7b375088866caf9

    We used its nine rest feature arrays, fixed pair selection, source metadata, and extraction code. We analyzed all 539 pairs and did not use its speech detector.

  2. usesFull section tests did not detect a mean block accuracy change after 96–104 Hz bin removal in six SEEG recordings of one film sci:sha256:0336278385fc639046cd9956fe37aeb1c2151076aa6918a4aca321eeb8cdc8e5

    The preserved source download code was adapted from this publication through the rest source publication. We retained its credit and MIT notice and used the code for fresh full-file checks.

  3. usesdoi:10.18112/openneuro.ds003688.v1.0.7

    The analysis uses rest recordings from OpenNeuro ds003688 version 1.0.7.

  4. doi:10.1038/s41597-022-01173-0
  5. doi:10.1038/s41467-017-02753-0

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