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Five-pulse estimates showed a greater mean 100 to 500 ms rise in repeatable power fraction at 2 to 30 Hz than at 70 to 150 Hz in eight STReEF SEEG runs

We tested whether the late increase in repeatable power fraction differs between two bands in public STReEF SEEG data. The fixed sample has eight patients, 96 conditions, and 6803 bipolar readout instances. All 960 fresh source ranges matched the pinned hashes. We used five pulses per group and corrected the power of their mean with off-diagonal pulse products. At 100 to 500 ms, the low-band minus high-band contrast was 6.84 percentage points. It was positive in 7 of eight patients. The exact two-sided patient sign-flip reference gave p=0.0156250. The descriptive 95 percent patient bootstrap interval was 3.54 to 10.42 percentage points. Fixed checks and every readout outcome are saved. The package includes figures, compact products, source versions and hashes, code, an estimator proof, independent checks, and retrieval instructions. The unbiased common-power claim needs a stable mean and uncorrelated pulse errors. The ratio is not unbiased. Repeatable voltage can include artifact. Before windows are not sham trials. The result does not test BCI accuracy or establish a neural cause.

SEEG · stimulation · repeatable power · spectral power · brain-computer interface · pulse variability

Admitted 6 citing publications

References

6
  1. usesDisjoint pulse products gave greater 20 to 100 ms SEEG energy estimates for common components than for components that change sign in eight sessions sci:sha256:3da7cd28bcc794882a9bb95c4148d0e2fc31e52bc0b8c0fb5d60085f1a5c893d

    We used its fixed 96-condition SEEG metadata selection and source-range SHA256 records. We downloaded all 960 source ranges again and computed new spectral products. Its time-domain outcome arrays were not inputs.

  2. usesA five-pulse check selected SEEG pairs with 60.8% mean shape agreement after contact order reversal at 20 to 500 ms in eight sessions sci:sha256:35cdaeabceeac5a3be97a54a264240386954c3bac2e4558f03b24d86d28e2bee

    We used its metadata selection method and three unchanged MIT source helper files to identify eligible conditions and retrieve pinned BrainVision byte ranges.

  3. doi:10.1093/sleep%2Fzsx077
  4. usesdoi:10.18112/openneuro.ds005448.v1.0.0

    STReEF OpenNeuro version 1.0.0 supplies the SEEG recordings analyzed here.

  5. doi:10.1016/j.ynirp.2025.100274
  6. doi:10.1007/s12021-022-09567-6

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