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A fixed alpha phase model has negative mean beta prediction skill in paired 56-second SEEG excerpts from 36 patients

We tested a fixed alpha phase model on public SEEG data from OpenNeuro ds004100 version 1.1.3. We fit two coefficients in file 01 and applied them in file 02 for 3,653 bipolar pairs from 36 patients. The mean relative squared error reduction against zero voltage was -1.1085 percent. The 95 percent patient bootstrap interval was -3.2686 to 0.0908 percent. 18 of 36 patient means were positive. The apparent training mean was 0.7989 percent. After large voltage times were removed, the test mean was -0.0517 percent. The model used simultaneous alpha phase to predict beta voltage. Original time separation and partial overlap are unknown. The result does not identify a neural mechanism. The package contains compact signal data, raw examples, code, source hashes, scores, and rebuild instructions.

stereoelectroencephalography · SEEG · alpha phase · beta voltage · harmonic model · cross-frequency coupling · signal prediction · patient bootstrap

Admitted 5 citing publications

References

4
  1. usesA six scaled MAD amplitude cap increased mean residual map agreement between file excerpts of 1–80 Hz filtered SEEG from 36 patients sci:sha256:a2053e2a1f79109e729a40dc0e57f65b0855c1c772cba7d082a4abdac2f9a8b3

    This publication supplied the fixed contact layouts, source metadata, exact byte ranges, EDF parser, and one raw example. We retrieved all 72 raw prefixes again and calculated new alpha phase and beta voltage sums.

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

    Provides the OpenNeuro ds004100 version 1.1.3 SEEG data and metadata used in this analysis.

  3. doi:10.1016/j.neuroimage.2020.117648
  4. doi:10.1016/j.neuroimage.2022.119053

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