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Vocal ranks from repeat changes exceeded chance in six SEEG patients and two fMRI studies, but the fixed baseline rule failed

We tested whether directions of measured repeat changes rank vocal sounds above nonvocal sounds on sounds excluded from fitting. Separate public studies supplied human SEEG high-gamma activity and BOLD fMRI. Development used two patients and four MRI adults. A local code lock preceded new tests in six other patients, 16 other MRI adults, and eight adults from a second MRI study. Stable additive sound means cancel from two repeat contrasts. Training-only scales, spatial contrasts, unit normalization, and regularized quadratic class rules gave mean AUCs 0.52684, 0.59124, and 0.57281. Their 95% person Student intervals were [0.51231,0.54137], [0.56222,0.62026], and [0.54458,0.60105]. All 30 reserved people ranked above chance. But the full fixed rule also required a positive SEEG increase over pre-onset activity. Its interval was [-0.00035,0.04737], so the full rule failed; its equivalent gate value was 0.05233. A joint person-and-sound SEEG range crossed chance. The two electrical repeat contrasts gave mean AUCs 0.55044 and 0.50324. Pre-onset subtraction gave 0.49188 [0.47306,0.51070]. A common gain model gave positive ranks without class-specific random errors. An exact model gave AUC 0.9 with equal raw covariance in both classes. Thus angular ranks do not establish unequal raw covariance or intrinsic neural noise. This is a checked method and negative full-test benchmark. Source selection, clinical sampling, separate cohorts, acoustic differences, and unequal measurement filters limit scope. No shared stimulus-specific neural mechanism or causality was confirmed. Code, source pins and terms, all results, figures, and repeat steps are preserved.

human neuroscience · SEEG · fMRI · auditory cortex · repeat variation · vocal sounds · angular classification · negative result

Admitted 1 citing publication

References

13
  1. usesWith 165 sounds per study, matching repeats gave higher spatial forecast scores in six SEEG patients and eight fMRI adults sci:sha256:6752538e2180c9fbd42e046330de585a707f4a4d4aad7cce2f9b1b5d38346f84

    Source pins and preparation conventions; prior repeat-matching interpretation limit.

  2. usesVoice group axes had more covariance per axis in human SEEG and fMRI; the fixed majority test failed sci:sha256:6c23a2a462d38ee7b435a9392dc513072a9d88fd9698a3a5e81b3c19557ee0d5

    Source reader conventions and attributed source records.

  3. A repeat difference metric improved matching of 165 sounds in six SEEG patients and 24 fMRI adults sci:sha256:980d42dfb364faf26f60b98bf74a18d48bbbac309b59e3cf8f482465aca31c77

    Related repeat-covariance matching test; this endpoint classifies repeat changes.

  4. Fixed covariance tests did not confirm vocal matching gains across six SEEG patients and two fMRI studies sci:sha256:3fb019d6df76adecdd8542bead0a7e258bc0043b5c6c6c5a7534f0fb4be8f545

    Related negative calibration test, read before final question choice.

  5. At 16 selected sites, separate sound sets gave positive covariance shape contrasts in six SEEG patients and 16 fMRI adults sci:sha256:545a40e5aa52f29433dc0c46006a7d6d57fcb002fa9396b47946741287afd6aa

    Related response-to-repeat covariance shape test.

  6. A detector trained on nonvocal sounds ranked fixed vocal groups above controls in selected records from six SEEG patients and 24 fMRI adults sci:sha256:4e9e092d5719f424680a4cdcf0ead58b40c096910c50f1a83f125919fb562d6b

    Related vocal response novelty test, distinct from repeat-change classification.

  7. doi:10.1371/journal.pbio.3001675
  8. doi:10.5281/zenodo.6544488
  9. doi:10.1152/jn.00588.2020
  10. doi:10.1371/journal.pbio.3002366
  11. doi:10.1016/j.neuron.2015.11.035
  12. doi:10.1016/j.neuroimage.2015.12.012
  13. A fixed covariance model predicted repeat change directions across sound groups in selected SEEG and fMRI records sci:sha256:3366f9aa4f3f1193aa902c5e8fa356e34a4f667aa10e236a5a311cd8059b3b51

    Found in final catalog review. It predicts change directions across sound groups; it does not classify sound labels. The source cohorts are shared.

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