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Voltage-distance selection gave higher mean five-site accuracy than response-strength selection in 15 bipolar SEEG tests from five patients, with amplitude retained

In public SEEG data from five patients, training-voltage distance selected five stimulation sites with 79.5% mean later-pulse identification accuracy. Selection by response strength gave 69.95%; random selection gave 46.85%. The mean distance-minus-strength gain was 9.55 percentage points. Its descriptive patient-bootstrap 95% interval was 5.60 to 13.25 points; the exact two-sided sign-flip p value was 0.0625. The gain fell to 2.0 points with one fixed recording pair per patient. Unit-norm selection and decoding reversed the gain to -19.35 points. The result is an offline, same-session calibration result with voltage amplitude retained. It does not establish a useful perception or a brain-writing effect. The package preserves code, public data provenance, epochs, pulse splits, predictions, tables, and figures. Independent prediction checks, a second analysis, and an exact raw-data epoch rebuild passed.

stimulation-site selection · stereoelectroencephalography · SEEG · voltage response · brain-computer interface · signal processing

Admitted 1 citing publication

References

4
  1. usesFour pulses gave better mean response ranks than one pulse in five offline bipolar SEEG tests sci:sha256:c9015b4b89ceffc195f0e36e740e7eae7d03e41d8ed41a831cef61e3e6bd2754

    Uses the saved trial epochs, source-study contact list, source hashes, and raw-data extraction code. Adds training-only stimulation-site selection and later-pulse tests.

  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

    Uses its early-response site-identification question as context. Tests a distinct five-site selection task and does not compare its accuracy values directly.

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

    The analysis used the version 1.0.2 OpenNeuro ds004457 dataset.

  4. doi:10.1523/JNEUROSCI.1325-22.2023

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