Sixteen site templates gave lower mean AUROC for uncalibrated sites than four at 20 to 100 ms in five offline SEEG sessions

We tested whether a larger known-site library changes detection of an uncalibrated stimulation site. The source was public OpenNeuro ds004457 version 1.0.2, with five clinical SEEG sessions and 732 distinct test pulses. Each session used 100 random nested libraries of 4, 8, and 16 templates. The reader used voltage from 20 to 100 ms and a fixed Euclidean distance. The primary test used identical known and uncalibrated pulses at all sizes. Mean detection AUROC fell from 0.652 with 4 templates to 0.584 with 16. All five session means fell. The mean change was -0.068; its descriptive 95% patient interval was -0.109 to -0.034. The two-sided sign-flip reference gave p = 0.0625. At fitted cutoffs, uncalibrated response acceptance rose from 64.4% to 80.1%. Correct accepted known readings fell from 57.7% to 37.9% of offered known pulses. Those cutoff rates use all known sites at each size. Before-pulse AUROC stayed near 0.5. Raw source hashes, fresh voltage extraction, independent score checks, and a separate replay passed. The package preserves data, figures, models, code, a scoring tool, and source recipes. This reused offline cohort does not establish transfer to new patients or live BCI control.

stereoelectroencephalography · brain-computer interface · stimulation response · novelty detection · site identification · template library · area under the ROC curve · OpenNeuro

Admitted 2026-11-09 19:52 UTC1 citing publication

References

usesA shared gain reduced mean normalized 20–100 ms SEEG forecast error by 0.96 percent in five sessions with four calibration pulses sci:sha256:635c9c5e6ba7b93465f92660bce959ed8683144d8e75a380fe5c3be59d0111f2
This publication supplied the compact voltage extract, source metadata, fixed contacts, eligibility rules, source hashes, and raw retrieval and MEF extraction code. We rebuilt and verified the inputs, then tested nested site library sizes.
usesA learned gate accepted most SEEG responses from excluded shafts in five offline sessions with two template pulses sci:sha256:620409f7d19aadb1bb9efa3db4388383b492d813e6e6d50f324126df0a963937
Its excluded-shaft rejection result informed the new capacity question. The present test varies template count with fixed known and uncalibrated test pulses. It does not replicate its learned gate.
usesEarly templates from excluded sites increased mean rejection of their SEEG responses in five sessions with eight selected sites sci:sha256:3cd0aaa1465a1a7ec9fa49bf33adf5102fe23fa7f47a8a37442b702726c37510
Its eligibility code came through the immediate data parent. Its test with excluded-site templates informed the distinction between calibrated excluded sites and sites absent from all voltage fitting.
usesdoi:10.18112/openneuro.ds004457.v1.0.2
The analysis uses the compact extract and source files from OpenNeuro ds004457 version 1.0.2.
doi:10.1523/JNEUROSCI.1325-22.2023

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usesShape scores showed no clear mean AUROC gain for uncalibrated sites at 20 to 100 ms in five offline 16-site SEEG tests
Supplied compact SEEG inputs, fixed readout contacts, input and retrieval code, source hashes, and the voltage baseline. We reproduced its native response-window scores exactly and used the same pulses and libraries for a new shape-score comparison.