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Two voltage checks accepted fewer correct responses than one check in five offline SEEG sessions at a 5% background calibration target

We tested a voltage check for feedback after brain stimulation. We used public OpenNeuro ds004457 version 1.0.2 SEEG data from five people with epilepsy. The main sample had 134 good stimulation sites on shafts separate from the recording shafts. Each site had three fit pulses, one calibration pulse, and four later test pulses. Both rules used a 5% background calibration target. A site check plus a response check accepted 23.1% of correct responses. A stricter site check alone accepted 28.1%. The mean paired change was -5.05 percentage points. Its descriptive patient bootstrap interval was -9.22 to -1.36 points. Matched before-pulse acceptance was 1.1% and 5.7%, respectively. One patient had too few calibration windows for a finite threshold, so both rules rejected all inputs. Only 32 of 536 test pulses followed all calibration data. These results show a rejection tradeoff in this fixed offline sample. They do not establish a live BCI benefit or a 5% error guarantee. The package preserves voltage inputs, all models and decisions, three figures, source hashes, code, and repeat instructions. Fresh raw recovery, independent arithmetic, and exact numerical replay passed.

SEEG · brain-computer interfaces · electrical stimulation · response detection · voltage signals · background calibration · rank thresholds

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References

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  1. usesA score against other known sites reduced wrong-site acceptance in five offline SEEG sessions sci:sha256:371f4f3b986f603932113c36983f8b3953578c6230974ac71b76da14a649b90b

    We used its compact public voltage inputs, fixed contact and pulse rules, and before-pulse failure result to choose this question. We recovered all inputs from pinned raw files. The new comparison reuses its patients and tests a separate response score against a stricter site score at the same background calibration target.

  2. usesA fixed covariance rule gave higher SEEG site accuracy than a diagonal rule in offline tests from five patient sessions sci:sha256:1407cd9ac712a4bcd551a3738cc90c3fab309b871572cbd6fc644b41555f7886

    The inherited extraction, retrieval, contact eligibility code, and fixed half-covariance model came from this work through the direct input study. We preserve the code credit and source record. We refit the common model with three fit pulses per site and add background means and response scores.

  3. usesPooling three background samples per site gave finite rank thresholds at a 5% target in six of eight SEEG patients sci:sha256:8d1d688adb68e371ba6248646ae992e104f6b8284d90d46541178480586649bc

    We adopted its finite rank threshold rule, explicit background sample budget, and global time audit. This prior work uses a different SEEG dataset. Our study does not claim a new rank method or an independent replication of its patient outcomes.

  4. usesdoi:10.18112/openneuro.ds004457.v1.0.2

    Source dataset, exact version used for the analyzed voltage inputs and event metadata.

  5. doi:10.1523/JNEUROSCI.1325-22.2023

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