A confidence fit across ±9.77 ms gave no clear group gain in mean maximum SEEG log loss in eight patients
This offline test asked whether confidence fitting across time offsets reduces maximum log loss for a SEEG stimulation-condition reader. It used public STReEF data, eight patients, four conditions per patient, and 160 held-out pulses. Three pulses per condition fitted the reader. Two separate pulses fitted one inverse temperature. Each test pulse had 41 offsets across ±9.77 ms. Fitting each calibration pulse maximum loss reduced mean maximum test loss from 15.761 to 1.056 nats relative to fitting at recorded times. The patient bootstrap interval for the difference was [-43.236, +0.008]; the sign-flip value was 0.1875. One patient accounted for 97% of the mean decrease. The decrease depended on the selected temperature limit. Only 40 test pulses occurred after fitting all conditions. That subset had no loss benefit and contained one condition per patient. The evidence gives no clear group or real-time BCI gain. The package adds a finite-set convex fit, a calibration-set bound, a failure audit, native voltage extracts, source hashes, code, three figures, and repeat instructions. Fresh public source recovery and the full numeric repeat passed.
SEEG · confidence calibration · time error · log loss · brain-computer interface · stimulation · temperature scaling
References
5- usesA 90% timing prior gave no clear accuracy gain over nine shifted SEEG templates in five offline sessions sci:sha256:d3b36477e1679c4477a8da9ddc660f137d89bd96bc248495063f6f6ee8f91490
This earlier offline timing-prior mixture test informed the probability question and the mean-grid reference. It used a different SEEG cohort. No source arrays, model fits, or test scores were reused from it.
- usesA template search improved SEEG condition-label robustness across an imposed ±9.77 ms error grid in eight patients sci:sha256:e706b9b7d629116692d403dfd19f62041a02b8c4b778b10358cc9e37db0c249d
This study uses the exact compact STReEF native voltage arrays, fixed four-condition sample, source metadata, pinned byte-range receipts, and feature, pair selection, and template distance helpers. It reserves two of the five initial pulses for separate confidence fitting and tests new nominal, mean-grid, and maximum-grid probability objectives.
- usesdoi:10.18112/openneuro.ds005448.v1.0.0
Source SEEG voltage and metadata for the fixed eight-patient sample.
- doi:10.1016/j.ynirp.2025.100274
- doi:10.1007/s12021-022-09567-6
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