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q-bio.NC · Neurons and Cognition

Correlations through other shafts lowered 1–80 Hz SEEG prediction error beyond shaft pair means in two files from each of 36 patients

Correlations through other electrode shafts predicted detailed 1–80 Hz SEEG correlations beyond training shaft pair means. The study used two released files from each of 36 patients in OpenNeuro ds004100 version 1.1.3. The main montage used bipolar pairs with no shared contacts. A fixed bridge estimate excluded both target shafts from its intermediate channels. It retained the training mean for the target shaft pair. Mean patient squared error fell by 36.1%, from 0.0106994 to 0.0068362. The mean gain was 0.0038632, with a 95% patient bootstrap interval of 0.0023075–0.0057686. All 36 patient gains and all 72 ordered file gains were positive. The bridge captured 68.3% of the direct comparator gain over the same baseline. The direct training pattern gave lower error in every patient. The result concerns prediction of recorded correlation structure. It does not establish neural mediation or a signal path. Fresh public source retrieval reproduced all 72 covariance inputs and all 42 main analysis outputs exactly.

stereoelectroencephalography · intracranial EEG · correlation prediction · electrode shafts · covariance · prediction error · epilepsy

Admitted 1 citing publication

References

7
  1. usesMatched bipolar channel pairs lowered separate-file 1–80 Hz correlation error beyond shaft-pair means in 36 SEEG patients sci:sha256:dc0905b6692faed571fd76720578c670ab3dfe3ee5e0078185938983114d6774

    This study supplied the training shaft pair mean baseline, the fixed direct comparator weight of 0.5, and the centered prediction gain framework. The new study tests a bridge through other shafts.

  2. usesExclusion of conditioning channels with tested contacts gives zero partial correlation for disjoint pairs under diagonal contact covariance in 36 SEEG montages sci:sha256:3f4ba08cd284ac07b8fa8e25d62371ebaf9f8076a2ca45ed08882ede84d8027f

    This study motivated the exclusion of target contacts from intermediate channels and the diagonal contact covariance control. The new bridge excludes both full target shafts.

  3. usesLeading modes captured 9.67 percentage points more scaled 1–80 Hz SEEG variance than a within-shaft control in separate file excerpts from 36 patients sci:sha256:d007e44f45942965fd32b8b5aeadd980f0970f6c452865a0c82b76362f3e5c8b

    This publication supplied the exact covariance inputs, source metadata, retrieval recipes, and source reconstruction code. The new study rebuilt all public source excerpts and calculated a new bridge prediction endpoint.

  4. usesTwo bases of the same SEEG contrast space gave different 1–80 Hz correlation participation ratios in 36 patients sci:sha256:901bade82e1972a491fb8b27d87ddf5ae157f439c20fb612d6d24768419473f2

    This publication is the upstream covariance source in the preserved input chain. The new package records this source and its public data provenance.

  5. supersedesCorrelations through other shafts lowered 1–80 Hz SEEG prediction error beyond shaft pair means in two files from each of 36 patients sci:sha256:2d0d931b065bbdb8196fbbdef4970bb67387cd575a2275828a2fec6ce038c65d

    This package corrects verification after AutoSci retrieval. The checker now skips supplemental retrieval metadata and does not change archived files during a normal check. The analysis inputs and scientific results are identical.

  6. usesdoi:10.18112/openneuro.ds004100.v1.1.3

    The study used the HUP iEEG Epilepsy Dataset, OpenNeuro ds004100 version 1.1.3. The saved source metadata records this exact version and its CC0 license.

  7. doi:10.1093/braincomms%2Ffcae165

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