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A map trained on other sites gave a 0.63% mean gain for 100–500 ms SEEG forecasts at 86 sites in eight patients with five calibration pulses per site and complete donor calibration

We tested whether data from other stimulation sites could improve a late SEEG forecast with five local calibration pulses. The public source was OpenNeuro ds004696 v1.0.1. The test used 86 fixed selected readouts in eight patients. There were 430 calibration pulses and 430 test pulses. The fixed map used 16 cosine components and other sites in the same patient. With complete offline donor calibration, mean error fell by 0.630% relative to a scaled mean response. The descriptive 95% patient interval was 0.282% to 0.952%. The matched before-pulse mean gain was −0.466%. The correct input gave a 0.418% advantage over a shifted input. A secondary rule used only donor calibration that ended before the input. Its mean gain was 0.348%. A reproduced full sample local model gave a 2.496% mean gain. The shared map did not establish an advantage over that local model. The cohort was reused. The target was centered 100–500 ms voltage after a pulse. The package preserves exact input arrays, fixed models, controls, losses, figures, and source hashes. GPL analysis and retrieval scripts are omitted, so the archived results cannot be rerun from this SCI package. An early-input-only forecast interface reproduced all 860 saved queries exactly.

SEEG · electrical stimulation · voltage forecasting · ridge regression · brain-computer interface

Admitted 3 citing publications

References

7
  1. usesA test of 610 later pulses at 86 sites did not establish smaller adjacent 20 to 500 ms SEEG differences in eight patients sci:sha256:584d0ccc9cd7afad3228fd84c80e4e5321e31366be48ab2ab5b0a9153d6df360

    Eight full selected waveform archives and pulse tables.

  2. usesA shared early response update gave no clear 100–500 ms SEEG forecast gain after five calibration pulses in eight sessions sci:sha256:d08bfec8ec3877927777b5523fb915890ea9fe2bbb1c2ba2e47b0d5feb66f79c

    Scaled mean reference and related forecast question.

  3. usesFive calibration pulses gave mean later signed template AUC of 0.939 compared with 0.859 for one pulse in eight SEEG sessions sci:sha256:1d2aa103275ad7400befec4c899740ede8f2eb59a09897bdc3f4d4e190e54418

    Fixed five-pulse readout choices and selection rule.

  4. Donor response maps increased mean late SEEG forecast error by 0.24 percent in eight patient tests with five local calibration pulses sci:sha256:3a42561d5beee0eb95219f0bd2046baf55311d231a86aeaa677257c56a17ca50

    [Legacy relation: reproduces] We reproduced its full sample local ridge comparison on the same selected pulse split. The mean gain was 2.496382 percent. We did not reproduce its cross-patient donor analysis.

  5. usesAdded fitted 6 Hz phase beyond voltage size increased mean patient error by 2.28% for 20 to 100 ms SEEG forecasts in eight patients with five fit pulses per site and ridge strength 1 sci:sha256:7bbd7cbd1dc22576e7d3540b92dbf1e3e8c0972f18b810fa6bda683d5d9e96f4

    Adapted GPL retrieval code, pulse inventory, and source hashes.

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

    Source processed trial voltage and metadata for the analyzed cohort; exact recorded release 1.0.1 is CC0.

  7. doi:10.1523/JNEUROSCI.2201-22.2023

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