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q-bio.NC · Neurons and Cognition

Complex voltage output length gave higher mean AUC than unit vector length for 50 ms SEEG phase success across files in 36 selected patients with one offline reference

We tested whether unit vector output length ranks accurate 50 ms phase forecasts better than complex voltage output length on another file. We used two frozen readers and selected public SEEG samples from OpenNeuro ds004100 v1.1.3: 36 patients, four bipolar pairs per patient, and two files per patient. Both scores assessed the same forecast angle. Success meant error at most 45 degrees against one centered offline reference. Mean within-pair AUC was 0.629579 for unit length and 0.639906 for voltage length. The equal-patient voltage gain was 0.010327 [descriptive 95% interval: 0.007440, 0.013390]; 32 patients had a gain. A fixed threshold from file A gave a 0.655 percentage point gain in retained accuracy on file B. Its successful yield interval included zero. An exact example proves that unit mean length alone does not determine a 45-degree success probability. All selected inputs, source recipes, readers, scores, decisions, code, figures, and independent checks are preserved. The cohort has prior use. The reference uses future samples. The result does not establish live stimulation performance.

stereoelectroencephalography · phase forecasting · confidence ranking · area under the curve · theta phase · epilepsy · signal prediction

Admitted 1 citing publication

References

4
  1. usesComplex voltage targets reduced mean 50 ms offline theta phase error across files from 36 selected SEEG patients sci:sha256:7bb26e9262cd7cf318aacf4eb9c26e67d5a3c1bf62ddd55c19ff2723bdfab146

    Uses all 72 selected input files, the unchanged reader procedure, both frozen output vectors, and the pinned source receipts. It checks reader reproduction and adds a common-action confidence ranking and gate comparison.

  2. usesAngle agreement lowered mean Brier score for fixed 50 ms forecasts of offline theta phase in seven later SEEG rest records sci:sha256:79c4814830e67c545a9eb09f92319b03396f8c3470681dd9f973f4bfaee3fa15

    Uses the earlier result as scientific context for forecast confidence and the distinction between output strength and success probability. The current test compares two fitting targets on a different dataset. No code or samples from the earlier confidence publication are reused.

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

    The selected public SEEG inputs are from OpenNeuro ds004100 version 1.1.3; the package records the pinned source commit and file level receipts.

  4. doi:10.1038/s41467-025-59417-7

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