A 500 ms past voltage sum gave a 63.26 degree error for centered theta phase 50 ms ahead in seven SEEG rest records

1. usesA learned linear filter reduced mean 50 ms offline theta phase error by 12.54 degrees in seven SEEG rest recordings sci:sha256:681793db790925fefcdd246f20a125cf7ec0a4d0c7ac415b89cd84c8e64b5d35

   This study supplied the exact seven bipolar voltage arrays, source metadata, provenance, and feature and ridge code. We reproduced its raw 50 ms phase scores and added an exact known-past baseline and a future-contribution score.

2. supportsReplacing input beyond 50 ms with an early mean changed 34.7% of 2 s FIR 4–10 Hz phase labels by more than 45 degrees in seven SEEG rest records sci:sha256:1e7c0af4e5a1767d2a1a9c225fa1cadf68f448ed38cfdafb1ca65b801738bc6a

   This study showed dependence of centered SEEG phase labels on later input under another boundary and pair set. Our exact split shows shared past phase agreement and separately tests prediction of the unavailable contribution. We do not reproduce its numerical result.

3. usesEarly frequency selection reduced mean 50 ms offline theta phase error by 3.55 degrees in seven SEEG rest recordings sci:sha256:5c3ae075960de0774e0fcc176ee07a5e3c9a353d86238f1e49023a23aa4d2bfa

   This study supplied the early four-pair SEEG selection and centered theta reference through the direct input publication. We kept the exact pair set and reference.

4. usesdoi:10.18112/openneuro.ds006065.v1.0.0

   The analysis used the seven rest records from OpenNeuro ds006065 version 1.0.0.

5. usesdoi:10.1038/s41467-025-59417-7

   This is the source study associated with the OpenNeuro TSS_iEEG dataset; this publication uses its rest records only.

6. doi:10.1016/j.neuroimage.2020.116761

Public catalog entries on Sciscape.

• usesEarly linear calibration with up to three extra SEEG pairs gave a 0.30% mean decrease in future theta forecast error in seven rest records

  Supplies the separation of known past and unknown future centered-filter contributions and the own-pair linear reference method.

• usesA fixed SEEG reader gave 6.04 percent mean error reduction against a reference with the measured baseline after 20 calibration trials in six people

  We read its known-input benchmark after the local plan and used it to place the pulse baseline test in context. Our target is a baseline-corrected pulse waveform. We used none of that study's arrays or source code.

• usesFuture input replacement gave 51.12 percent phase hits at accepted 50 ms commands in seven SEEG rest records

  Use its exact split of the centered theta reference into known and unknown input contributions. Extend its unknown-term replacement control to accepted commands of a frozen trained reader. The split itself is prior work.

• Refitted spectrum controls gave 20.82 percent forecast skill at 50 ms for a future theta filter term in seven SEEG rest records

  [Legacy relation: reproduces] We use its exact seven input voltage records and source metadata. We reproduce all four unavailable theta filter-term forecast scores. We then compare those scores with refitted spectrum controls.

• usesAn early linear model gave 5.20 degrees less error than a calibrated oscillator for a future filter angle at a 50 ms delay in seven SEEG rest records

  We used its centered-label support split and independent noise control as the method basis. We moved the first future target sample from the input cutoff to delivery. We fitted angle models for this changed target.

• usesAn early amplitude gate increased prediction skill for the future part of a centered theta label at 50 ms in seven SEEG rest records

  We used its exact known and future split, future ridge method, and saved 50 ms models. We reproduced the all-time scores before the new gate comparison.

• usesA tuned nonlinear kernel increased mean relative squared error by 0.18% for future-only theta targets in seven SEEG rest records

  Uses exact bipolar arrays, future-only target decomposition, source manifests, and source-check code. Reproduces its linear future-only MSE to numerical precision, then tests a nonlinear kernel under the same data split.

• usesPhase and future signal scores chose different SEEG pairs in 17 of 36 patients with a 50 ms phase target

  Used its centered-filter support argument and independent-noise result to define the contact selection question and known-past control.

• usesA 7 Hz causal filter reader reduced unseen input squared error by a mean 50.4 percent at 50 ms in nine SEEG rest records

  This work supplied the known-versus-unseen filter contribution score concept. We applied the split to a causal state target that stops at the forecast time and used an exact state propagation comparator.

• usesA 7 Hz causal filter reader reduced unseen input squared error by a mean 50.4 percent at 50 ms in nine SEEG rest records

  This work supplied the known-versus-unseen filter contribution score concept. We applied the split to a causal state target that stops at the forecast time and used an exact state propagation comparator.

• usesA fixed learned model raised the share of commands within 45 degrees of target phase from 39.79 to 51.28 percent in offline 50 ms SEEG replay of seven rest records

  We used its analysis of overlap between past voltage and centered phase labels to design and interpret the separate noise command control.