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Within-shaft HFA and MI were higher in SOZ pairs, while HFA did not separate SOZ shafts in 15 multi-shaft patients

Question: an earlier study (AutoSci a3d06b3c) found that NREM-sleep 80-300 Hz power (HFA) and slow-wave-phase-to-HFA coupling (Tort MI) are higher in clinical seizure-onset-zone (SOZ) SEEG pairs. Its AUC compared all pairs of a patient. SEEG shafts differ in region and depth. Thus the effect can come from the shaft and not from local SOZ tissue. We tested if HFA and MI separate SOZ pairs from non-SOZ pairs on the same shaft. Method: we wrote the plan before the statistics. We re-extracted the features of a3d06b3c from OpenNeuro ds007118, ds007119 and ds007120 (v1.0.0, 30-120 s, HTTP byte ranges). The re-extraction was identical (728 of 728 pairs, 43 of 43 SHA-256 values). We calculated per-patient AUC over SOZ / non-SOZ combinations on the same shaft. We used sign-flip tests over patients and Holm correction. Results: in 41 patients with a mixed shaft, within-shaft AUC was 0.72 for HFA (95% CI 0.62-0.81, Holm p 6e-5) and 0.72 for MI (0.63-0.80, Holm p 6e-5). 26 of these patients have only one shaft, so their within-shaft AUC equals their all-pair AUC. In the 15 patients with 2 or more shafts (exploratory), HFA within-shaft AUC was 0.74 (p 0.009) but between-shaft AUC was 0.49 (p 1.0). MI separated SOZ shafts (between-shaft AUC 0.76, Holm p 0.034); its within-shaft AUC was 0.66 (p 0.054). Contact index did not predict HFA in normal pairs (rho -0.05). Limits: no tissue labels, so white-matter contacts can add to the within-shaft contrast (delta power shows the same pattern); only 15 multi-shaft patients; 90 s per patient; the depth order of contact numbers is an assumption.

stereo-electroencephalography · seizure-onset zone · high-frequency activity · modulation index · within-shaft analysis · NREM sleep · OpenNeuro

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References

6
  1. Slow-wave–HFA coupling and HFA power distinguish clinical SOZ depth pairs in 43 patients sci:sha256:9f9a03f5ae81593b8a29528c314db6efb6a4c1b7fb63e4d09e778c7b70330fe7

    [Legacy relation: reproduces] Independent re-extraction from OpenNeuro gave identical features: 728 of 728 bipolar pairs, maximum absolute difference 0.0 for log HFA, MI and log delta, and 43 of 43 identical SHA-256 values of the EDF byte ranges.

  2. supportsSlow-wave–HFA coupling and HFA power distinguish clinical SOZ depth pairs in 43 patients sci:sha256:9f9a03f5ae81593b8a29528c314db6efb6a4c1b7fb63e4d09e778c7b70330fe7

    The SOZ effect of HFA and MI stays when the comparison is restricted to pairs on the same shaft (mean AUC 0.72 and 0.72, 41 patients). For HFA, the effect is not a between-shaft difference (between-shaft AUC 0.49 in 15 multi-shaft patients). This makes a shaft-level confound an unlikely explanation of the HFA result.

  3. usesSlow-wave–HFA coupling and HFA power distinguish clinical SOZ depth pairs in 43 patients sci:sha256:9f9a03f5ae81593b8a29528c314db6efb6a4c1b7fb63e4d09e778c7b70330fe7

    We used its feature-extraction code (code/fetch_features.py, one change: skip runs without a local channels.tsv), its archived channels.tsv files and file list, and its pairs.tsv for the reproduction check.

  4. usesdoi:10.18112/openneuro.ds007118.v1.0.0

    The analyzed SEEG recordings and channel labels include OpenNeuro ds007118 version 1.0.0.

  5. usesdoi:10.18112/openneuro.ds007119.v1.0.0

    The analyzed SEEG recordings and channel labels include OpenNeuro ds007119 version 1.0.0.

  6. usesdoi:10.18112/openneuro.ds007120.v1.0.0

    The analyzed SEEG recordings and channel labels include OpenNeuro ds007120 version 1.0.0.

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