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Fixed speech models had mean squared test error of 0.919 with past and current amplitude and 0.958 with future and current amplitude in five SEEG patients

We tested whether past speech amplitude improved fixed models of selected SEEG high gamma power when both past and future models also included current amplitude. Using OpenNeuro ds004703 version 1.1.0, we selected one contact pair per patient and fitted ridge models on 20 early passages, then tested on 23 later passages from five patients. Mean squared test error was 0.91944 with past and current amplitude and 0.95810 with future and current amplitude. Four of five patient differences favored past amplitude. The mean future-minus-past difference was 0.03866 (95% t interval -0.00115 to 0.07847; exact two-sided sign flip p=0.125). An assumed 40 ms audio shift reduced the difference to 0.01360. This small, non-independent reanalysis did not establish a group difference or neural cause. The original results, figures, predictions, and analysis code are retained. Source recordings, metadata, event records, and extracted input caches are linked but omitted because ds004703 source statements conflict: its metadata says CC0, while its README restricts commercial use and participant identity analysis.

stereoelectroencephalography · speech amplitude · high gamma power · ridge regression · temporal prediction

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References

7
  1. supersedesFixed speech models had mean squared test error of 0.919 with past and current amplitude and 0.958 with future and current amplitude in five SEEG patients sci:sha256:857bf7fe868d92da0161fee353471613e5dc8995c9f8797ebab11e161de609b9

    This version corrects the package manifest. The first archive contained every file, but the package manifest omitted upstream/MANIFEST.json. The corrected manifest includes that file. The scientific results are the same.

  2. usesSEEG pairs selected on early speech had positive later envelope correlations in four of five ds004703 patients sci:sha256:4ca065abc950fa470e382f3e05718bd6f9b27245d537e6cae7d9b8cce991ca40

    We used the complete feature package, early contact pair rule, public source metadata, extraction code, and byte provenance. We added fixed encoding models and a later-passage comparison of past and future audio. We rebuilt all 43 selected-pair passages from pinned source bytes.

  3. usesdoi:10.18112/openneuro.ds004703.v1.1.0

    Source SEEG recordings and speech audio were from OpenNeuro ds004703 version 1.1.0; source terms and input omissions are described in the main text.

  4. doi:10.1371/journal.pone.0053398
  5. doi:10.3389/fnhum.2016.00604
  6. supportsdoi:10.1088/1741-2552%2Fabb25e

    This study supplies background evidence that acoustic contamination can affect intracranial electrophysiology during speech and sound perception.

  7. supportsdoi:10.1016/j.neuroimage.2022.118962

    This study supplies background evidence about speech vibration artifacts in intracranial recordings.

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