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Frequency weights raised mean minimum site coverage from 63.5 to 89.8 percent in five SEEG sessions when 80 percent of simulated commands used one shaft and site responses stayed fixed

We tested whether known command frequencies can improve stimulation-site prediction sets. We used 171 sites and 342 test pulses from five public SEEG sessions. Each simulated command mix assigned 80 percent of commands to one shaft. The response distribution at each site stayed fixed. Across all 38 shaft policies, the patient mean of minimum correct-site coverage rose from 63.5 to 89.8 percent with frequency weights. Four weighted policies still had coverage below 90 percent. Mean candidate count across policies was 10.31, but it grew at the policies with lowest original coverage. In 16 policies, the small calibration sample forced all favored-shaft sites into the set regardless of voltage. The package supplies a cutoff tool, compact data, source hashes, figures, and reproduction code. A fresh raw rebuild and a separate repeat matched exactly. This exploratory within-session result does not give a coverage guarantee for future pulses or live BCI use.

stereoelectroencephalography · prediction sets · label shift · coverage · electrical stimulation · brain-computer interfaces · calibration

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References

4
  1. usesPooled site sets included the correct site for 93.6 percent of later SEEG pulses within five sessions at 20 to 100 ms sci:sha256:16a0821e6ea5302515dea9c46cffb63ec910cd0b438ee578fb5d0ecad4563dc7

    We used its exact compact data, cohort, pulse roles, fitted readers, probability arrays, pooled cutoffs, and source recipe. Equal site weights reproduced its sets. We added fixed shaft command-frequency policies and candidate-specific weighted cutoffs. The same five sessions are reused and do not form an independent patient replication.

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

    This is the original compact-bin and raw extraction source inherited through the immediate parent. We retained its contact and event rules and extraction credit. A fresh download of the pinned public subset and raw reconstruction matched every compact data file exactly.

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

    The study uses the five-session OpenNeuro ds004457 v1.0.2 source data; the saved source manifest records the exact file URLs, sizes, and SHA-256 hashes.

  4. doi:10.1523/JNEUROSCI.1325-22.2023

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