A margin guard certified audit sign stability under bounded additive error in five public SEEG sessions
We tested a sign guard for one audit pulse from a known stimulation site. We used five public SEEG sessions from OpenNeuro ds004457, version 1.0.2. The guard uses a metric fixed from calibration pulses. Each template projection must exceed a stated additive error bound in magnitude. The proof shows that accepted signs must agree with the error-free audit under that bound. All 13,526 accepted main window cases with simulated nonzero error met this condition. Directed errors at the planned radius changed signs in four selected audits. The guard rejected all four. A site rule based on calibration template length accepted 61.09% of cases at the planned metric radius of 8. The inherited consistency rule accepted 59.49%. The mean paired difference was 1.60 percentage points across five sessions. An exact descriptive sign-flip test gave p = 0.50. These data do not give clear evidence of a general selection benefit. The certificate does not prove physical wiring signs or correct site predictions. A valid device error bound remains necessary. Only 27 of 549 source targets followed all fit pulses and the selected audit. No live interface was tested. The package preserves the proof, code, voltage bins, source hashes, results, figures, and a checked raw retrieval recipe.
SEEG · audit sign stability · bounded additive error · brain-computer interface · intracranial EEG · robust signal processing
References
4- usesOne pulse at a known site restored signed SEEG reader decisions under fixed output sign reversals in five sessions sci:sha256:6608efa990f24ae14041238702ba102f41544786550a11aba45224db5967a920
We used its known-site single-pulse sign estimator, calibration-only consistency site rule, and reserved-audit split. We reproduced its five selected sites and nominal target decisions. The new study adds a sign-stability guard under bounded additive audit error and tests a template-length site rule.
- usesAbsolute pair scores kept SEEG site decisions fixed under simulated output sign reversals in five sessions sci:sha256:8a26582c314b8be03ef05d9206ae910fa50daac8c1ccee11c5df2d7794d6821e
We used its fixed SEEG cohort, binned voltages, source metadata, covariance reader, and retrieval and extraction code. We freshly retrieved all 110 pinned source files and rebuilt the bins. All arrays and event-table bytes matched. Its absolute-cosine reader supplies the no-audit comparator.
- usesdoi:10.18112/openneuro.ds004457.v1.0.2
The five analyzed SEEG sessions and source files are from this exact OpenNeuro version; the archived manifest records the retrieved file paths and hashes.
- doi:10.1523/JNEUROSCI.1325-22.2023
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