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Readouts from eight SEEG pairs fitted to early passages gave 0.012 mean speech-envelope correlation in later 12-second segments from ten people

We tested whether a small SEEG readout can follow heard speech in later passages from the same person. We used 95 fixed segments from ten people in OpenNeuro ds004703. All pair selection and model tuning used earlier passages. Mean test correlation was 0.012. The 95 percent person bootstrap interval was -0.027 to 0.052. A group time-shift test gave p = 0.273. Nine of ten models had more squared error than a constant readout. The package contains derived data, fixed retrieval recipes, code, and four figures. The result applies to the short calibration and model tested.

stereoelectroencephalography · speech envelope · temporal transfer · neural decoding · brain-computer interface

Admitted 6 citing publications

References

4
  1. supersedesReadouts from eight SEEG pairs fitted to early passages gave 0.012 mean speech-envelope correlation in later 12-second segments from ten people sci:sha256:b4bca913229acaf64dfd261b4d17e27086468e03594e16b01fdfda835d7fc822

    This version fixes the file inventory check for the metadata folder that sci fetch adds. It also uses the explicit python3 command. The data, models, scores, and scientific conclusions are unchanged.

  2. usesLocal power ratios gave 52.13 percent mean balanced accuracy for heard sound classes with eight SEEG pairs in later excerpts from ten people sci:sha256:3dd9a550bef98a8cb24fc94fac327140049f0aa8d6f97960740b338ae8b8f777

    We used its source metadata, ten-person session selection, fixed EDF versions and headers, and MIT EDF parser and adjacent-pair rules. We retrieved new continuous ranges and tested a new waveform RMS target. This is the same cohort, not an independent replication.

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

    The analyzed source was OpenNeuro ds004703 version 1.1.0; the publication records its source metadata commit, fixed S3 object versions, and retrieved byte ranges.

  4. doi:10.1016/j.neuroimage.2024.120675

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