sciscape Publications
← All publications

Covariance gates increased mean rejection of faulty and recorded inputs under simulated contact gain 4 in eight offline SEEG tests

We tested two input gates on public SEEG data from eight people with epilepsy. The gates used 24 band-power features from eight bipolar pairs. Early trials set the pairs, decoder, and gates. Separate early trials set a nominal 5% rejection threshold. Later trials were held for testing. We changed one physical contact at a time before bipolar subtraction. Neither gate received the changed contact or the true class. At the primary voltage gain of 4, the covariance gate rejected 97.70% of faulty inputs. The diagonal gate rejected 95.76%. They also rejected 5.34% and 3.16% of recorded inputs. All rejection rates are equal person means. The primary difference in fault rejection minus recorded rejection was -0.24 percentage points. The descriptive 95% person bootstrap interval was -1.92 to 1.52 points. The exact person sign-flip probability was 0.796875. The primary test did not show a clear covariance advantage. Gains of 2, 0.25, and 0 gave different rejection tradeoffs. Many gain-loss inputs passed both gates. We preserve exact selected voltage samples, all scores, source checks, code, and three figures. The complete numeric repeat matched exactly. This is an offline test with artificial faults. It does not establish live BCI performance.

brain-computer interface · stereoelectroencephalography · input rejection · covariance gate · fault simulation · abstention · contact gain

Admitted 2 citing publications

References

4
  1. usesPower ratios kept 67.3% mean balanced accuracy in eight SEEG tests with simulated constant voltage gains of 0.5 to 2 per pair sci:sha256:c8d319ab758f561272e7079e3140f325e48fe460e476a2dc9cb20baa67b25f68

    Used its bipolar-pair gain scope to define a separate physical-contact gain question. Here a gain acts before bipolar subtraction and the gate has no fault-location input. No result arrays from that study were copied.

  2. usesSample clipping raised mean balanced accuracy from 56.5% to 63.8% under simulated 1 mV, 10 ms contact faults in eight SEEG recordings sci:sha256:76e13d01e49a34d263825687c9046fad559ed2ce66b54a45f100bcc1237bee88

    Used its retained trial records, eligibility rules, candidate fit features, source range hashes, EDF extraction helpers, and logistic code. Fresh source ranges reproduced all selected features exactly. The new test fits unknown-contact gain gates and reports abstention costs.

  3. usesdoi:10.18112/openneuro.ds004473.v1.0.2

    The study used the ds004473 version 1.0.2 source recordings and metadata; the source metadata specify CC0.

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

Cited by

2 publications

Public catalog entries on Sciscape.