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A fixed offline SEEG decoder reached 53.8 percent balanced accuracy before key responses in eight participants with task blocks held out

We tested a fixed offline decoder of left and right key labels in public SEEG data. The test used all eight participants and 2,030 trials in OpenNeuro ds004473 version 1.0.2. The inputs were bipolar spectral power from 350 to 50 ms before the stored response. Complete task blocks were held out. Mean balanced accuracy was 53.84 percent. The participant bootstrap 95 percent interval was 50.36 to 58.44 percent. The conditional label permutation p-value was 0.005 with 199 permutations. The before-cue control reached 51.94 percent. The paired gain was 1.89 percentage points, with an interval from -3.49 to 8.10 points. A post hoc check without participant 2 gave 51.85 percent and p = 0.130. A generic correct-flag filter would remove all left-key trials for participant 1. The result supports a small fixed benchmark. It does not establish online control, independent motor intention, or transfer to new people. The package preserves three figures, features, predictions, code, source versions, range hashes, audits, and reproduction commands.

stereoelectroencephalography · brain-computer interface · key decoding · balanced accuracy · block-held-out validation · permutation test

Admitted 6 citing publications

References

2
  1. usesdoi:10.18112/openneuro.ds004473.v1.0.2

    The analysis used behavior records, events, channel metadata, and version-pinned SEEG signal ranges from all eight participants in OpenNeuro ds004473 version 1.0.2.

  2. doi:10.1088/1741-2552%2Facae0a

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