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Growing means gave no clear gain above a random order reference for 20–500 ms SEEG forecasts in eight patients

This study asks if past pulse responses improve SEEG forecasts beyond the gain from a larger mean alone. It uses public OpenNeuro ds004696 version 1.0.1 and the same eight patients as prior sci studies. There are 86 included stimulation sites and 886 site/readout combinations. Each forecast uses only completed past retained responses. For a fixed set of ten waveforms, the study proves an exact mean error reference under random pulse order. The proof does not require independent pulse noise. In the primary 20–500 ms window, the growing mean gain above this reference was 0.0092 in normalized error units. The descriptive 95% patient interval was -0.0038 to 0.0250. A joint order test gave p=0.144 under stated patient independence and pulse exchangeability assumptions. The full-window test gave no clear evidence of extra growing gain from the recorded order. This does not prove fixed responses or pulse independence. Secondary early-window and recent-mean results were more favorable. The recent gain was sensitive to the scoring scale. The package preserves a proof, compact voltage data, event maps, five figures, source hashes, and retrieval instructions. GPL analysis and extraction scripts are omitted, so the exact archived analysis implementation is unavailable for public rerun. It preserves exact analysis replay checks and two fresh public source reconstructions. This is an exploratory cohort reanalysis. It does not test a clinical benefit or an online controller.

SEEG · brain-computer interface · voltage forecasting · randomization test · pulse order · forecast calibration

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References

6
  1. usesPower weights fit from five pulses gave no clear mean 20–500 ms SEEG voltage forecast gain in eight sessions sci:sha256:5f8ad290d211abb81202a82ed21683bfe60c8df22cceb4e18c340cf2fc14ee28

    This study copies the all-pulse voltage products, pulse maps, native examples, metadata, and source retrieval code. Their fixed hashes permit the new forecast contrast and its source checks.

  2. usesForecast updates reduced 20–500 ms SEEG error by 3.1 percent compared with a fixed five-pulse forecast in eight patient sessions sci:sha256:35785d9e2db7ec2ea2c6a6c6786f024d2492f7c5d43f940d2d9f21e30c4a2bb3

    The prior growing-mean gains motivated the question. This study uses an unscaled mean and an exact finite-set order reference. It reuses the eight patients and supplies no independent replication of the prior variance-scaled endpoint.

  3. Recent five-pulse updates with noise scaling reduced mean 20–500 ms centered bipolar SEEG forecast error in eight patient sessions sci:sha256:aab0f09b0cde0fe33fe1115134d13702f7c2609ff81a1be8300ff8d84b1ea5be

    [Legacy relation: reproduces] The added audit reproduces only the prior unscaled mean point estimates under the first-five mean power score: growing gain 4.851 percent and recent gain 0.383 percent, within 0.001 percentage points. It does not reproduce the main variance-scaled endpoint. The audit followed primary outcome inspection. Its bootstrap seed differs.

  4. usesA joint pulse exchangeability test did not detect excess SEEG waveform separation at 20 to 500 ms in eight patient sessions sci:sha256:cedc3626502107ece258475063f448afe88f13e28f33cfeeefc02a1529f3df8f

    The prior joint pulse order test informed the use of a shared within-patient rank permutation. This study tests forecast gain above an exact larger-mean reference. It does not repeat the prior waveform separation test.

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

    This study uses OpenNeuro ds004696 version 1.0.1 for the eight-patient SEEG reanalysis.

  6. doi:10.1523/JNEUROSCI.2201-22.2023

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