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Local 2 s beta baselines gave no clear gain over transferred baselines for post-stimulation correlation forecasts in eight SEEG patients

We tested whether a local 2 s beta baseline gave a better post-stimulation correlation forecast than a baseline from another record. We used all 22 records from the eight patients with repeated records in public OpenNeuro ds006519 version 1.0.0. Each of 48 ordered record pairs used matched contacts and edges between different shafts. The beta band was 13 to 30 Hz. Patients had equal weight. Mean squared error was 0.03546 for the local baseline and 0.03534 for the transferred baseline. The transferred-minus-local difference was -0.000114. Its descriptive 95 percent patient bootstrap interval was -0.000771 to 0.000441. The exact patient sign-flip p value was 0.765625. The test did not establish a local gain or equal performance. A fixed zero-correlation forecast had 43.4 percent less error than the local baseline. Both baseline errors were higher than zero error in each patient. The target was a noisy sample estimate. The sign-flip test assumes independent patients and symmetric null differences. Contact masks assume that the supplied bipolar pair labels describe the montage. Record order was not verified. No live interface or stimulation policy was tested. The package preserves input arrays, all forecast cases, source hashes, code, three figures, and raw retrieval instructions. Independent checks passed, and raw extraction reproduced all 22 input arrays exactly.

stereoelectroencephalography · SEEG · beta band · brain-computer interfaces · functional connectivity · correlation networks · forecast error · baseline transfer

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References

6
  1. usesBeta power ranks have higher agreement than beta network strength ranks between 3 s baselines in eight SEEG patients sci:sha256:dd8a1ee586c1a7276d197e8b391188542f3b8a9603e2240b0f58a49961c495b7

    Its low agreement of beta network strength ranks motivated this forecast question. We use the same repeated-record cohort, but test post-event signed correlation error with patient weighting.

  2. usesEarly products showed no clear gain over squared means for ten beta SEEG pairs per record in 21 patients sci:sha256:f69098b6590697b26076a3652b3849afb77d2e232c5dd3435085c4a2818421aa

    We use its exact 22 event arrays, reviewed extraction and retrieval code, contact parser, and source identity checks. We rebuilt the arrays from the public source and checked every field.

  3. usesA baseline rule reduced later beta SEEG correlation error in 1 s windows from 21 patients sci:sha256:05572bbfd69c0cd02a49e72246e6e438e50bf8fda0ee17b297b3702b9d6fccab

    Its extraction, retrieval, contact parser, and separate beta window methods were inherited through the input publication. Its within-record shrinkage test gives context for the fixed half-scaling control. We test substitution between records.

  4. usesdoi:10.18112/openneuro.ds006519.v1.0.0

    This is the exact OpenNeuro dataset release used for the repeated-record cohort.

  5. doi:10.1016/j.neuroimage.2026.121822
  6. supportsdoi:10.1093/braincomms%2Ffcae165

    This study supports the report’s limitation that intracranial EEG network estimates depend on reference and connectivity choices.

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