Rest calibration gave a 4.2 percent mean false positive rate in eight later-trial SEEG tests

We tested separate rest calibration in eight public SEEG recordings from OpenNeuro ds004473 version 1.0.2. Earlier trials trained eight-pair logistic models. Separate earlier rest windows set a nominal 5 percent rank threshold. Later tests gave 4.2 percent mean false positive rate and 27.5 percent mean pre-response sensitivity. Participant bootstrap 95 percent intervals were 2.5–5.8 percent and 12.7–46.1 percent, respectively. The same models at score 0.5 gave 29.8 percent false positives and 68.2 percent sensitivity. Calibration reduced both positive decisions and sensitivity in all eight recordings. Three recordings exceeded 5 percent observed rest error. Under an ideal independent-sample model, small calibration sets left 21–41 percent probability of population error above 5 percent. This is an offline test of event-aligned task states within each recording. It does not establish continuous intention detection or a practical command gate. The package preserves 2014 trial features, code, models, predictions, three figures, provenance, and reproduction commands. A fresh rebuild matched all feature arrays and 2032 source range hashes. A second analysis matched all eight numerical result files exactly.

stereoelectroencephalography · brain-computer interface · rest calibration · false positive rate · split conformal calibration · pre-response sensitivity · electrophysiology · offline evaluation