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Site variation scales give mixed probability gains in five SEEG sessions with three template pulses and separate calibration

We tested whether each pulse site needs a separate trial variation scale. We used public SEEG data from five epilepsy sessions, 183 sites, and 732 test pulses. Both readers used three early template pulses per site, a common covariance shape, and separate probability calibration on fourth pulses. For responses from 20 to 100 ms, mean test log loss was 3.358 bits per pulse with a shared scale and 3.348 with site scales. The mean gain was 0.010 bits per pulse. Three patients had a gain and two had a loss. The descriptive patient interval was -0.013 to +0.039 bits per pulse. Mean accuracy was 31.80% and 31.78%. With temperature fixed at one, site scales increased loss in all five patients. These data do not establish a consistent gain from site scales with this fitting budget. Tests were later within each site, but most occurred before fitting ended at other sites. This is an offline extension on a reused cohort. The package preserves figures, inputs, code, fitted models, all test probabilities, source hashes, and reproduction instructions. A raw-data rebuild and a second analysis run matched the preserved data and numerical results exactly.

stereoelectroencephalography · brain-computer interface · electrical stimulation · probability calibration · site variation · log loss

Admitted 1 citing publication

References

4
  1. 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 archived ds004457 version 1.0.2 voltage bins, metadata, target contacts, eligibility rules, raw-file hashes, and extraction code. We adapted its loader and rebuilt its inputs from public raw files. This enabled a paired test of shared and site-specific variation scales.

  2. usesEight selected sites raised accuracy in all five SEEG sessions but raised log score in four sci:sha256:6ea14d902f7540805304f1e86e0d9539a65d008e19a638b20889ef52c0a3d361

    We used its three-template and fourth-pulse probability-fit split, fixed one-percent uniform probability mixture, and held-out log-score procedure. We kept all eligible sites and tested variation scales. We did not use its selected site sets.

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

    Analyzed source dataset, version 1.0.2; the recorded dataset metadata identifies it as CC0.

  4. doi:10.1523/JNEUROSCI.1325-22.2023

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