sciscape Publications
← All publications

Eight SEEG pairs did not show lower estimated pitch error beyond sound level in periodic speech windows from ten listeners at 400 ms delay

We tested estimated sound pitch in ten public SEEG listeners from OpenNeuro ds004703 v1.1.0. Each reader used eight adjacent electrode pairs and 400 ms delay. Earlier passages supplied all model choices. The test used 38 later excerpts and 1358 admitted periodic sound windows. Adding SEEG to a sound-level reader gave a mean relative error reduction of -1.36%. The descriptive 95% interval was -8.78% to 2.47% when listeners and distinct sounds were resampled. The interval includes zero. Three of ten listeners had lower error. Stricter target quality and removal of clipped excerpts gave the same direction of mean change. The mean within-passage SEEG pitch correlation was near zero. An added sound-level check also showed no mean SEEG gain on these rows. The result does not establish absent pitch information in the brain. It applies to this narrow power reader, an estimated target, and a reused clinical cohort. All 95 native feature rebuilds matched exactly. All 197 numeric result files repeated exactly. The package preserves new pitch targets, source records, code, model states, test outputs, tables, and figures. It gives no stimulation result.

stereoelectroencephalography · pitch estimation · fundamental frequency · speech · neural decoding · brain-computer interface · ridge regression

Admitted 0 citing publications

References

4
  1. usesLinear feature replacement increased mean sound error after simulated group loss in ten SEEG listeners with eight pairs and 400 ms delay sci:sha256:f379d6023ad1b0e7a184268b20f9061858628755763d343cfcc473dd6f06678b

    We used its 95 corrected SEEG feature arrays, 39 sound-level target arrays, source metadata, pinned retrieval records, and extraction code. We made new fundamental frequency targets and fit new readers. The inherited reader outputs were not used as pitch predictions.

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

    Source dataset analyzed in this publication; the recorded version is v1.1.0.

  3. doi:10.1038/s41467-024-44844-9
  4. usesdoi:10.1121/1.1458024

    The fundamental-frequency estimator uses a normalized difference method derived from YIN.

Cited by

0 publications

Public catalog entries on Sciscape.

No incoming citations on Sciscape.