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q-bio.NC · Neurons and Cognitionstat.ME · Methodology

Relative distance gave smaller site sets in five offline SEEG sessions at 20–100 ms with a 90% calibration target

We tested public stereoelectroencephalography (SEEG) data from five patient sessions. The test used 183 fitted stimulation sites and 732 test pulses at 20 to 100 ms. A relative score subtracted the smallest candidate distance from every candidate distance. At a 90% calibration target, mean set size fell from 17.4 to 11.7 sites. Each patient had equal weight in the mean. Mean correct-site inclusion was 91.1% for raw distance and 90.9% for relative distance. All five patients had smaller relative sets. The longer response window reduced relative inclusion to 85.4%. A proof and a constructed check showed that relative sets can ignore some changes in response energy. The package has checked source data, code, models, figures, and a fixed set reader. The offline split does not establish future coverage or live interface performance.

stereoelectroencephalography · SEEG · candidate sets · Mahalanobis distance · conformal calibration · intracranial stimulation · uncertainty

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References

7
  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 the public source manifest, MEF retrieval and extraction code, and native 5 ms voltage bin rule. The new package preserves this code and a hash-checked retrieval recipe.

  2. 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

    Its probability-based site sets motivated the uncertainty question. We used its report to define the prior scope. Its different cohort and pulse split prevent a matched numerical comparison.

  3. usesWith a common distance metric, a site mean projection kept labels but changed response rejection in five SEEG sessions sci:sha256:89a0f4b75951c86751075c3a8c471fa0a885e897a901f86e53edef1c6a020892

    We used its mean-span distance identity to explain a common distance term. Our proof applies that identity to fixed candidate sets, and a constructed feature check tests the limit.

  4. 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 the saved voltage bins, fixed recording contacts, site rules, and covariance model. We rebuilt the raw inputs and compared raw and relative candidate scores on the same fitted model.

  5. usesA template gap gave 0.827 mean error AUROC across known sites in five offline SEEG sessions at 20 to 100 ms sci:sha256:dc63492a24a9ea283c3614ac0cb44e52c40919816b33c87d0a619dfb6a649bb8

    Its nearest-distance gap results helped define the prior work on these 183 sites. We tested a distinct candidate score: each site distance minus the nearest site distance.

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

    The analyzed voltage bins and event metadata were derived from OpenNeuro ds004457 version 1.0.2; the saved source record identifies this exact release and its CC0 license.

  7. doi:10.1523/JNEUROSCI.1325-22.2023

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