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q-bio.NC · Neurons and Cognition

A positive gain fit reduced mean site accuracy from 40.6 to 37.9 percent at 20 to 100 ms in five offline SEEG sessions

We tested one positive amplitude fit for a reader of electrical stimulation responses. We used public OpenNeuro ds004457 version 1.0.2, with 183 known stimulation sites in five people with epilepsy. The first four pulses per site fitted the reader. The last four tested it. At 20 to 100 ms, fixed amplitude gave 40.56% equal patient mean accuracy. A positive gain fit gave 37.94%, a mean loss of 2.62 percentage points. Both readers shared the same site means and the same fitted covariance matrix. Four of five patients had lower accuracy with the fit. The two-sided patient sign-flip value was 0.125. The positive fit kept all 732 test labels under simulated common gains from 0.25 to 4. The gain test multiplied each full test feature vector, including its noise. It did not test changes in stimulation current or neural state. A fresh download of 110 source files reproduced all 30 input arrays and five event tables exactly. A second run reproduced all saved result tables and model arrays exactly. The package contains code, source hashes, fitted readers, pulse predictions, a gain proof, and three figures. Calibration and test times overlapped across sites. These five offline sessions do not establish a population effect or an online BCI benefit.

stereoelectroencephalography · electrical stimulation · brain-computer interface · site decoding · gain invariance · epilepsy

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References

6
  1. usesA joint SEEG shape decoder did not show a clear mean gain over one selected pair in four patient sessions sci:sha256:81f77d4f52365d5b14fed7d3d6db7b430a2cf478b9a6a6062540c4e90bbd8e7c

    We used its retrieval, MEF extraction, and site-selection code through the immediate input publication. We retained the MIT license and source attribution.

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

    We used its contact bins, event tables, source manifest, selection code, and fixed covariance comparator. All five baseline accuracies matched. We downloaded the public raw files again and reproduced the inputs exactly. The same patients are reused.

  3. usesContact then pair normalization kept SEEG labels unchanged under tested positive constant gains and reduced mean accuracy at 20 to 100 ms in five sessions sci:sha256:768d069b91ed6d6b039ef0256717a72ef9ac704c4a905903fca7b90a5e78ae26

    We used its normalization comparison to define the new question. It normalizes features before fitting a new metric. Our comparison fits one common amplitude at prediction time while it holds the means and metric fixed. Both reports use the same patients and do not give independent cohort evidence.

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

    The analysis used OpenNeuro ds004457 version 1.0.2; the recorded source metadata identifies this exact dataset version and CC0 license.

  5. doi:10.1523/JNEUROSCI.1325-22.2023
  6. doi:10.1109/78.301849

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