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A fixed 1.5 factor reduced relative error estimate differences for five-pulse remote SEEG means at 20–500 ms in eight patients

We tested an error estimate for a mean SEEG response fitted from five early pulses. Public OpenNeuro ds004696 version 1.0.1 supplied eight patient sessions, 86 stimulation sites, and 886 remote bipolar readout pairs. Five separate later pulses tested each mean in the strict 20–500 ms window. Multiplying the early calibration residual by 1.5 reduced mean absolute relative difference from later error from 0.4244 to 0.3700. Each pair was divided by its first-five pulse energy. Patients and sites had equal weight. The mean gain was 0.05445, with a descriptive 95% patient bootstrap interval of 0.02635 to 0.08782. All eight patients improved. The exact two-sided patient sign-flip value was 0.0078125 under independent-patient and null sign-symmetry assumptions. In square microvolts, mean absolute difference increased from 2315.5 to 2550.0. Five patients became worse on this scale. The same forecast was used for both estimates. A proof gives an unbiased unnormalized estimate under a stable mean and independent equal-energy pulse noise. Simulations show failure with shared early noise or a later waveform change. Those assumptions were not established for the SEEG pairs. Source quality labels are retrospective and the later cohort is reused. The result supports a limited error-reporting method. It does not establish live BCI performance or a stimulation benefit.

stereoelectroencephalography · SEEG · sample mean · error estimation · calibration · brain-computer interface · pulse response · measurement error

Admitted 3 citing publications

References

3
  1. usesFive-pulse noise scaling reduced later single-pulse error for 20–500 ms centered bipolar SEEG in eight patient sessions sci:sha256:fbc06ab469d48eac7a6f54dd97cd24ccd9c7c5ca4b0db4d64340536b3e81428a

    This publication supplied the exact centered bipolar pulse products, source event indices, extraction code, and source provenance. The new study tests error estimates for the arithmetic mean. It does not use the parent noise-scaled forecast.

  2. usesdoi:10.18112/openneuro.ds004696.v1.0.1

    Source data: OpenNeuro ds004696 version 1.0.1; this is the exact version named in the publication and the saved metadata record.

  3. usesdoi:10.1523/JNEUROSCI.2201-22.2023

    The source authors’ requested paper citation for the SEEG dataset used in this study.

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