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A fixed voltage reader had less mean 50 ms phase loss under three offline references in 36 selected SEEG patients

We tested two fixed 50 ms phase readers in 36 selected patients from public SEEG data. Both readers were fit to one 2 s offline reference. We scored unchanged predictions against 1, 2, and 4 s references on 80,640 matched queries. The voltage reader had less mean cosine loss at all three spans. The gains were 0.01097, 0.01080, and 0.01213. The three simultaneous 95% patient bootstrap intervals were above zero. The preferred reader changed in 7 patients and 25 of 144 pairs. Five patient changes remained with a 0.0001 loss margin. Exact limits for query-specific phase arcs certified the voltage preference in only 5 patients. These arcs contain the tested reference angles. They do not bound biological phase. This exploratory audit preserves native data, fixed models, code, source records, query results, three figures, and a public retrieval recipe. The study does not test live stimulation or clinical benefit.

SEEG · phase estimation · neural signals · offline reference · cosine loss · ridge regression · signal processing · epilepsy dataset · reference sensitivity

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References

3
  1. usesThree references gave 4.58 percentage points less joint 45-degree agreement than one for nominal 50 ms forecasts with a fixed gate in 36 SEEG patients sci:sha256:5268b4ce23f89bc64468fe68204498f55e145e9276e73fc21deb962d962f5542

    This study supplies the 1, 2, and 4 s reference design, the matched cutoff range, and the public prefix retrieval code. We use these methods to test the comparison of two fixed readers.

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

    This publication supplies the exact selected native data, two fixed reader models, inherited code, and source records. We use them to compare both readers under three offline references. We also check the archived predictions.

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

    The selected SEEG records are from OpenNeuro ds004100 version 1.1.3; the recorded dataset metadata identifies this exact release and its CC0 license.

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