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Tests on excluded sound classes did not confirm shared gains from four spectral terms in 16 iEEG patients and 16 fMRI adults

We tested whether four mean spectral coefficients improve response predictions for an excluded sound class. Separate human studies supplied signed intracranial field means and BOLD fMRI. Each model fit within-class acoustic slopes in four classes and tested centered responses in the fifth. Seven base terms described pitch, loudness and harmonicity. A local lock preceded new endpoint tests in 16 iEEG patients and 16 MRI adults. Mean added gains were +0.339 and +1.054 points of centered response error. Pointwise 95% person Student limits were [-0.303,+0.980] and [+0.412,+1.696]. The fixed shared gain-and-skill test failed, p=0.14657593. Eight adults from another MRI study had an uncertain added gain. All negative people and classes remain. A crossed fixed-model sound/person range also included zero for primary MRI gain. Complete-refit gain ranges included zero in every study. We supply 199 complete nested refits per study, all draw weights and all person results. A fixed-site proof shows invariance to class-specific response offsets and nonzero site gains. Independent least squares, exact source-chunk checks and clean score replays passed. These are new endpoint tests in reused public data, not new prospective cohorts. Clinical sampling, different sounds, tasks, source screens, extraction builds and measurement filters limit scope. No positive cross-modal neural effect, absence of spectral coding or causal relation was established. The package gives a checked negative benchmark, efficient exact refit tools, permitted inputs, provenance, all scalar outcomes, figures and repeat steps.

human neuroscience · intracranial EEG · fMRI · auditory cortex · spectral shape · sound classes · nested validation · negative result

Admitted 2 citing publications

References

14
  1. usesExploratory A1 and belt models improved prediction in 12 of 13 iEEG patients and all 16 fMRI adults on fixed sounds sci:sha256:e23c7d60934cfd68c27b80a6551ac7933a03bf2a24d4ed536175f7463d9a0613

    Licensed compact inputs, source pins, feature table, source readers and attribution.

  2. usesTests with one sound class left out did not confirm shared gains from seven loudness terms in 21 iEEG patients and 24 fMRI adults sci:sha256:d3d02aa730feca9c77f9ebc0c5c88e457777e864d0d5152f5c506e02391bd485

    Related sound-class exclusion benchmark; our endpoint removes response class offsets and tests a different feature block.

  3. usesWith clipped acoustic inputs, pitch and voice feature gains changed sign with ridge penalty in human iEEG and fMRI sci:sha256:e95662f5edfdc91e5a27d6897bd91cdcd9c5939c16ab922e19e4a6967923fd5e

    Feature-gain interpretation limit and regularization comparison.

  4. usesFixed tests did not confirm shared animal–voice transfer in both directions in 16 iEEG patients and 16 fMRI adults sci:sha256:dd12d810575623b9cfbc032e9aec64eaabc11ea3b21b4a2cdf3d93f29d4c244c

    Attributed exact baseline chunk map for a fresh public source audit.

  5. doi:10.1523/JNEUROSCI.1388-12.2012
  6. doi:10.1016/j.cub.2026.07.063
  7. doi:10.1371/journal.pcbi.1003412
  8. doi:10.1371/journal.pbio.3002366
  9. doi:10.5281/zenodo.20599001
  10. doi:10.1152/jn.00588.2020
  11. doi:10.1016/j.neuron.2015.11.035
  12. doi:10.1109/TAFFC.2015.2457417
  13. doi:10.1145/1873951.1874246
  14. doi:10.1016/j.cub.2022.01.069

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