For fixed auditory tables, exact sampling risks favored a common estimate over means from four sounds per class in 19 of 21 iEEG patients and 0 of 24 fMRI adults
We tested whether acoustic correction improves short maps of auditory class means. Separate public studies supplied human iEEG voltage and BOLD fMRI. Four patients and four MRI adults supplied development. A local code lock preceded new endpoint scores in 21 patients and 16 other MRI adults. Each panel used four sounds per class across five classes. A split acoustic rule corrected each half using slopes fit on the other half. Mean error gains were 0.224% in iEEG and 0.568% in primary fMRI. Their 95% person Student limits were [0.106,0.341]% and [0.526,0.610]%. Mean electrical skill versus one common calibration estimate was -61.586%, with limits [-89.192,-33.981]%. MRI skill was +42.396% [39.775,45.017]%. The shared gain-and-skill rule failed, p=0.999980. An added exact finite-library calculation compared ordinary class means with the common estimate. At four sounds per class, ordinary means had greater expected error in 19 of 21 electrical patients and none of 24 MRI adults from two studies. A closed form rule gave every feasible count threshold and oracle shrinkage factor. The added calculation is exploratory and conditional on the fixed processed tables. It does not identify a causal modality difference. Baseline subtraction left electrical gain uncertain. A one-site MRI control had negative skill. Full sound deletions, every negative result, direct regression checks and exact small-table enumeration remain. The package provides a checked estimation tool and negative cross-modal accuracy benchmark. It does not confirm a positive biological generalization, absent class coding, or prospective time savings. Code, permitted inputs, source pins and terms, full results, figures and repeat steps are supplied. Original MRI arrays stay external.
human iEEG · fMRI · auditory cortex · category means · finite population sampling · control variates · negative result
References
18- usesAt 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 sci:sha256:ff51441a87d6dd1f0c2567c840e07fbb6d344674d061956664d946ef0266b5be
Licensed compact data, source readers, source pins and class crosswalks.
- supportsA fixed sound panel test did not confirm shared gains in 20 iEEG patients and 16 fMRI adults sci:sha256:c90376886d6419357431a8357251ec70bda279f1cbafd1079c06ded4813c5d2a
Prior benchmark motivates separate accuracy and relative-gain tests.
- supportsA fixed 32-sound selection rule failed its shared accuracy test in 21 iEEG patients and 16 fMRI adults sci:sha256:a0abdbef73995ed3f222f465976df5b0c4fa661217dd44fcb5be6909676f96e1
Prior acoustic selection test motivates the absolute accuracy gate.
- usesMaps fit to other sound classes predicted fixed animal sound patterns in 20 iEEG patients and 16 fMRI adults sci:sha256:1b8693e8389d334be8780044f5056e91081fd0c71bf35ea03565a0b417773b48
Inherited licensed electrical extract and audit lineage.
- usesOne bit per auditory site gave mean four-class accuracy above chance in 20 iEEG patients and 16 fMRI adults sci:sha256:640399d48b2742bcc4d3c828910fda08a928b409a54c25a630f3a8b53642c0c2
Inherited public byte-range reader and source extraction map.
- usesTwo fixed acoustic rules did not confirm shared nonvoice prediction gains in 18 SEEG patients and two fMRI groups sci:sha256:f6ade96a55abd5dd6909603449b3d63ad197279407aa009d924a3be21ddc98ae
Inherited licensed MRI acoustic descriptor measurements.
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Cited by
3 publicationsPublic catalog entries on Sciscape.
- Vocal labels failed shared forecast tests in 14 iEEG patients and 16 fMRI adults
Related finite-table class-mean risk and sampling precision.
- usesFor fixed sounds, mean acoustic transfer gains were positive in SEEG and two fMRI studies; the test for every class failed
Supplies licensed compact inputs, source pins, crosswalks and the MIT MRI reader.
- usesAt 60 sounds, allocation transfer raised mean sampling risk in fixed tables from 18 iEEG patients and 16 fMRI adults
We build on its exact finite-library class mean risk method, and test a new allocation transfer endpoint.