A fixed acoustic distance rule failed shared error tests in 20 iEEG patients and 16 fMRI adults

We tested whether acoustic distance from fitting sounds warns of large neural model errors. Separate public studies supplied human intracranial EEG and BOLD fMRI. Four people per study supplied development. A local code lock preceded tests in 20 other patients and 16 other adults. The fixed reader used nearest acoustic distance after feature clipping. It ranked errors after control for sound class, fold and predicted response size. Mean rank associations were +0.0054 [-0.0369, +0.0477] and +0.1134 [+0.0750, +0.1518]. Brackets give pointwise 95% person Student limits. A gate removed high-distance sounds within class and fold. Mean gains over matched random removal were -3.2362 [-6.2926, -0.1798] and +2.7839 [+2.2578, +3.3100] percent of whole-panel error. Both shared tests failed; Holm P values were 0.792091 and 0.980458. Eight adults from another MRI acquisition had a positive mean adjusted association, but uncertain gate gain. One separate B2021 estimate had an association interval across zero. A three-voxel check also left gate gain uncertain. An exact rank split showed that between-class terms reversed the raw MRI association. A later transform swap showed that clipping changed electrical gate results. These checks do not establish a modality effect or a cause. The package gives a fixed error warning benchmark, permitted inputs, source pins and terms, all results, code, figures and repeat steps. Fixed sounds, incomplete acoustic features, clinical coverage, source screening, noise and separate cohorts limit scope. No positive cross-modal error warning was confirmed.

human neuroscience · intracranial EEG · fMRI · auditory cortex · encoding models · error warning · acoustic distance · selective prediction · data reuse