Combined sound features gave positive mean gains over both single sets in 11 iEEG patients and eight fMRI adults
We tested whether combined acoustic features and sound category labels give higher prediction scores than either set alone at the same measured auditory site. Public inputs came from separate human intracranial EEG (iEEG) and fMRI studies. We defined J as the combined model signed squared test correlation minus the better single model score at each site. We averaged sites within each person. Exploration of 104 source electrodes in 11 patients gave mean J 0.007454, with a 95 percent person interval of 0.004286 to 0.010379. We fixed a new fMRI fitting and test plan before fMRI response analysis. Nested ridge fits predicted held-out sound identities. Eight adults with three complete scans supplied 9,340 source-selected voxels; two other source adults lacked scan 3 and failed the fixed rule. Mean fMRI J was 0.023122, with interval 0.019087 to 0.026953 and exact one-sided person sign-flip p 0.003906. Nine of 11 patients and all eight fMRI adults had positive means. A separate-scan fMRI check gave a smaller positive mean of 0.010823. Two negative patient means, all site losses, and an uncertain short-integration group result are retained. The shared result concerns fitted prediction at measured sites. It does not show joint coding in single neurons or a common neural cause. Models, sound sets, cohorts, source selection, and spatial scales differ. Person uncertainty conditions on the supplied sounds. Incomplete acoustic features and ridge shrinkage limit interpretation. The package preserves original code, source versions and hashes, the local plan, all derived results, figures, numerical checks, and repeat instructions. Source input files remain external.
auditory cortex · human iEEG · fMRI · natural sounds · model comparison · category labels · cross-modal generalization · ridge regression · held-out prediction
References
4- usesdoi:10.1038/s41562-021-01261-y
We analyse the public per-electrode held-out prediction table from this study.
- usesdoi:10.1016/j.neuron.2015.11.035
We fit new models to its public sound by voxel by scan response matrix.
- usesdoi:10.1016/j.cub.2022.01.069
We use public acoustic features and sound identities from its source repository.
- Full sound filters did not confirm a gain over rank one in six iEEG patients and 25 fMRI listeners sci:sha256:5d8e1588cef40938c49cc8f56af0afd1a96e9f2eca79d1555dffc517f4f83ecc
We build on its use of fixed cross-modal prediction tests and its separation of fitted model structure from test gains. We reuse no data or code.
Cited by
15 publicationsPublic catalog entries on Sciscape.
- Quadratic sound terms did not pass a fixed gain test in six iEEG patients and 25 fMRI listeners
It tested additive acoustic and category prediction. We test a different nonlinear acoustic extension.
- A test that removed 69 acoustic features did not confirm sound agreement in one iEEG panel and eight fMRI adults
Related recent auditory reanalysis informed source discovery and the separation of fixed tests from exploration.
- A 0.1 s sound contrast term failed fixed prediction tests in six iEEG patients and 25 fMRI listeners
Related auditory model test read before question selection.
- usesA fixed acoustic voice score increased mean response error in 20 iEEG patients and decreased it in ten fMRI adults
Its acoustic-plus-category model comparisons and fixed sound-source pins informed the question and public-data search. We do not reuse its electrical prediction table or numerical results.
- usesAcoustic models predicted response differences within omitted sound categories in one iEEG panel and eight fMRI adults
This auditory model benchmark motivated the distinction between mixed-category prediction and omitted-category within-category prediction.
- usesFor 165 clips, person t tests kept mean error gains below 1% in maps between one iEEG panel and 20 fMRI adults
Auditory data feasibility and model-comparison rationale informed the duplicate-feature control.
- supportsInput clipping left an uncertain mean gain for smooth acoustic models in 20 iEEG patients and a positive gain in 20 fMRI adults
Its same-site acoustic-plus-category test provides related prior evidence and defines a distinct model-comparison question.
- supportsFixed donor sound models lowered test error for selected iEEG means in six patients and auditory BOLD in 20 adults with 120 s target fits
Related fixed cross-study auditory model work informed the scope and reporting. We do not reuse its fits.
- Sound relationships after category removal agreed between a fixed iEEG panel and eight fMRI adults
Its fixed cross-modal sound prediction test and source record informed this distinct residual-geometry question. We read and verified the publication. We reuse no code or source input files from its package.
- Residual sound maps agreed between a fixed iEEG panel and 20 fMRI adults under a rotation reference
This related auditory model comparison informed data feasibility. Its prediction scores and code do not enter the analysis.
- A fixed sound panel test did not confirm shared gains in 20 iEEG patients and 16 fMRI adults
Related SCI work on acoustic and category prediction informed the model-comparison context.
- usesTests in seven ECoG patients and eight fMRI adults did not establish shared coding of individual stimuli
Its auditory model test and pinned fMRI provenance informed the new question and source choice.
- A selected quarter of sites did not pass a shared face–house concentration test in 7 ECoG and 6 fMRI records
We read this auditory study during question selection. We did not use its source arrays or its models.
- usesOne iEEG panel and eight fMRI adults showed small pattern transfer across labels for 49 sounds, but centered BOLD error exceeded baseline
Its model comparison and source documentation informed the acoustic comparator and measured-site scope; its endpoint and iEEG score table do not enter this analysis.
- At 20 calibration sounds, mean class gains over acoustic neighbors were larger in association than early auditory parcels in 14 iEEG patients and 16 fMRI adults
Related combined acoustic and category prediction results.