A positive definite EEG contrast model permits every selected channel partial correlation between minus one and plus one under unrestricted common signal covariance
We test whether EEG voltage differences fix absolute channel partial correlation. The proof assumes a positive definite contrast covariance and unrestricted covariance of the missing common signal. For each selected pair, the same contrasts permit every partial correlation strictly between minus one and plus one. We give all positive definite covariance completions and a finite magnitude bound. An alpha band audit used 88 processed records from OpenNeuro ds004504 version 1.0.9 and a normalized contrast ridge of 0.001. All 15,048 record pairs allowed correlations below minus 0.992 and above plus 0.992 in separate completions. The package also gives an unsigned residual variance fraction. Its largest change across 24 shared reference conditions was 4.520e-13. All primary pairs passed separate Schur complement checks. Two fresh source downloads matched 128 saved windows. A full offline repeat matched every numerical result. The variance score depends on ridge, channel set, and earlier processing. The package preserves code, input matrices, source hashes, construction parameters, proof, figures, and repeat instructions.
EEG · covariance completion · partial correlation · voltage reference · contrast covariance · linear prediction · ridge regularization
References
8- usesCommon average reference changes posterior theta-to-alpha ranks in 88 ds004504 v1.0.9 records with source processing fixed sci:sha256:2047e7d0ae35196950f5421eb9237a3b0a817c451fabcbdedd0b92ad776f3431
This study produced the 6,377 band matrices from 88 public records. We preserve its extraction code, source manifest, and license.
- usesAverage reference increases alpha edge counts below minus 0.5 in 88 ds004504 v1.0.9 records at normalized ridge 0.001 sci:sha256:78515fba17bce8b5e233e2c94bb559bff7c1e15d4ebe4804dda52960b5d02148
We reuse its unchanged EEG matrix archive and source records. Its average reference audit defined the starting question.
- usesA fixed EEG model predicts shuffled labels when training and test sets share the 88 ds004504 subjects sci:sha256:7ba0bee1f809898d24fefdeb839b4d53689a26bcea0ff0429014af5f5ef0c2a9
The inherited retrieval code adapts this publication. We use that code for the two new source checks and preserve its license notice.
- usesdoi:10.18112/openneuro.ds004504.v1.0.9
The public EEG audit uses processed records from this exact OpenNeuro dataset version.
- doi:10.3390/data8060095
- doi:10.1109/ACCESS.2023.3294618
- doi:10.1007/s11571-026-10464-w
- doi:10.1016/j.acags.2020.100026
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