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Early pulse calibration selected eight sites with higher later SEEG identification accuracy than random sets within site blocks in five patients

We tested whether early pulses can select stimulation sites with distinct later SEEG responses. We used 1,923 pulses at 185 sites in OpenNeuro ds004457, version 1.0.2. The first half of pulses at each site supplied calibration data. The second half supplied separate test data. A fixed rule selected eight sites for each of five patients. Mean site identification accuracy was 82.1 percent. Uniform random sets reached 41.8 percent. The gain was positive in all five patients. Its descriptive patient bootstrap interval was 30.9 to 50.6 percentage points. The exact two-sided patient sign-flip p value was 0.0625. Selecting the strongest responses reached 79.6 percent. The evidence did not show a clear gain over that simpler method. Signals before the pulse reached 11.1 percent for the selected sets, against 12.5 percent chance. The package preserves signals, code, all sets, predictions, three figures, source hashes, and raw retrieval instructions. Complete raw extraction and separate scalar checks passed. The test halves shared stimulation blocks and sessions. Calibration was earlier within each site, but not earlier than all test pulses across the recording. The result does not establish new-session performance, distinct percepts, or useful clinical control.

stereoelectroencephalography · electrical stimulation · site identification · calibration · brain-computer interfaces

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References

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  1. usesThree early valid 6 mA pulses per site selected sites with greater later SEEG voltage energy than random expectation in five patient sessions sci:sha256:2986e9c79b14eb86379a6faea58142d182aaac35b734ad23f0dd1db049ae222a

    Its early-to-later site calibration question informed our comparison with response-size selection. Our outcome is site identification accuracy. We did not import its code or data arrays.

  2. usesSEEG response shapes at 15–100 ms gave higher site identification accuracy than shapes at 100–500 ms within each of five patient sessions sci:sha256:aa5b71d76d214f861e99964287f9da01f3f9fc6c707a4dcfe24807283918ab40

    We use its public SEEG signal bins, event rows, source hashes, fixed contact pairs, and unchanged raw retrieval and extraction code. Its early-window result motivated the tested interval. We add calibration-only selection of sets of eight sites and later-pulse comparisons.

  3. usesdoi:10.18112/openneuro.ds004457.v1.0.2

    Source dataset snapshot used for the signal bins and verified raw file extraction.

  4. doi:10.1523/JNEUROSCI.1325-22.2023

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