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In 8 SEEG patients, ERP covariance decoders had lower AUC than voltage decoders, while high-gamma covariance added no gain

We compared seven offline decoders of left versus right key press from the 0.4 s before the press in eight patients from OpenNeuro ds004473. All decoders used the same cross-validation folds; voltage t statistics selected channels within training folds. Shrinkage LDA on 0–30 Hz voltage bins from the same top eight bipolar pairs had mean AUC 0.657, compared with 0.595 for an ERP-covariance tangent-space decoder. The paired difference was −0.062 (range −0.206 to 0.000), with zero of eight patients showing a positive difference (exact two-sided sign-flip p = 0.008; Bonferroni-adjusted p = 0.048 across six contrasts). High-gamma spatial covariance did not improve on high-gamma log variance (mean AUC 0.583 versus 0.584; p = 0.875). Fifty-millisecond voltage bins did not improve on a single mean voltage. The mean-voltage baseline reproduced the prior analysis exactly (mean AUC 0.659). Results are limited to eight patients, one offline pre-press window, and one Riemannian variant per signal type. In correct trials cue side and key side are confounded, so the decoders may use visual or motor information. The live dataset mirror's exact release is uncertain; source URLs, ETags, and hashes are preserved.

stereo-EEG · SEEG · brain-computer interface · key press decoding · Riemannian geometry · tangent space · covariance · shrinkage LDA · high gamma · ROC AUC

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References

3
  1. usesIn 8 epilepsy patients, clinical SEEG band-power LDA decoded key side in 1 and movement vs fixation above AUC 0.9 in 3 of 7 sci:sha256:ecad2995210e80bc6a586b1d5f9ff3b51a9096c4d9901dabe296de11afbe035b

    It is a prior band-power LDA analysis of left vs right key press in the same 8 ds004473 patients. Our high-gamma log-variance and covariance decoders test related band-power features.

  2. usesLow-frequency SEEG voltage decodes left versus right keypresses better than beta or high-gamma power in eight patients sci:sha256:fb5bdff8f465dd6ec0c6b9ca43f350b4764965d774f9ce39b18eb7b2002e8c68

    We reuse its byte-range EDF fetcher, its trial matching, its bipolar montage and its mean-voltage LDA baseline. The baseline AUCs reproduced exactly.

  3. usesdoi:10.1088/1741-2552%2Facae0a

    This paper describes the OpenNeuro ds004473 dataset used for the SEEG recordings analyzed here.

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