Two selected SEEG pairs had higher mean response detection error than eight pairs after condition changes in eight people
We tested how the number of selected SEEG pairs affects an offline brain reader after a task condition change. We used OpenNeuro ds004473 version 1.0.2 and eight people with epilepsy. Each model used 64 early calibration trials. The later test set contained 979 trials. Two selected pairs had mean response detection Brier error 0.2133. Eight pairs had error 0.1996. The mean increase was 0.0137, with a descriptive 95 percent person bootstrap interval of 0.0025 to 0.0264. The exact sign flip probability was 0.0703. Mean balanced accuracy was 66.66 percent with two pairs and 69.69 percent with eight pairs. Left versus right key accuracy remained between 51.22 and 52.96 percent across six budgets. Mean key Brier error did not improve on the constant 0.5 output at any budget. The result separates response detection from key reading when testing recording input requirements. These test trials were used in earlier sci work. The response windows use future event times. The results are exploratory and do not establish performance for a live interface. The package preserves code, input arrays, source retrieval recipes, models, scores, figures, and independent checks.
stereoelectroencephalography · SEEG · brain-computer interfaces · pair selection · Brier error · condition transfer · response detection · key reading
References
3- usesEight SEEG key readers gave 53.4 percent mean balanced accuracy after condition changes with 32 calibration trials sci:sha256:b9d997feb12a06acbb687e7dfcfe304892654f63871ce3f774503880b6647dbe
We used its candidate SEEG power arrays, recovered trial arrays, event joins, metadata, input loader, and pinned retrieval recipes. These files supplied the inputs and source checks for the new pair budget and probability error tests. We fit all models again and audited one fresh voltage range for each person.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The analyzed SEEG and task records came from OpenNeuro ds004473 version 1.0.2; saved metadata identifies this exact version and its CC0 license.
- doi:10.1088/1741-2552%2Facae0a
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