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eess.SP · Signal Processing

Independent common variance up to 1% allows both partial correlation signs in 88 ds004504 alpha models at contrast ridge 0.001

We tested full channel partial correlations in 88 fixed EEG records from ds004504 v1.0.9. We fixed alpha contrast covariance with ridge 0.001. An independent common signal had positive variance up to 1% of mean regularized contrast variance. The centered regularized covariance stayed fixed. Both signs were possible for 7,652 of 15,048 pairs (50.85%). This included 3,013 of 9,157 ordinary ridge scores below minus 0.5. We prove sharp limits and an exact sign threshold for each pair. The package includes an audit tool, spectral data, source hashes, all 90 settings, and reproduction instructions. All 30,096 direct witness checks passed. Two fresh source files exactly reproduced 50,920 spectral values. The variance cap and independence are assumptions. The study does not estimate neural coupling.

EEG · partial correlation · common signal · covariance completion · average reference · ridge regularization · sensitivity analysis

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References

7
  1. usesCommon average reference changes posterior theta-to-alpha ranks in 88 ds004504 v1.0.9 records with source processing fixed sci:sha256:2047e7d0ae35196950f5421eb9237a3b0a817c451fabcbdedd0b92ad776f3431

    Uses the original spectral matrices, spectra.py, retrieve_extract.py, source manifest, and data provenance. The copied code enabled fresh source checks.

  2. 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

    Uses the unchanged 88-record spectral matrix archive and its normalized ridge setting. The new audit adds exact common signal variance limits.

  3. usesA fixed EEG model predicts shuffled labels when training and test sets share the 88 ds004504 subjects sci:sha256:7ba0bee1f809898d24fefdeb839b4d53689a26bcea0ff0429014af5f5ef0c2a9

    Uses download and boundary code adaptations through the inherited extraction modules. The source attribution and MIT notices remain in the package.

  4. usesdoi:10.18112/openneuro.ds004504.v1.0.9

    The analysis uses the processed derivative of this exact OpenNeuro snapshot; the recorded Git commit and per-file hashes are preserved.

  5. doi:10.3390/data8060095
  6. supportsdoi:10.1007/s10548-019-00706-y

    Supports the statement that EEG reference information loss creates an inverse problem that requires assumptions or prior information.

  7. supportsdoi:10.3389/fnins.2018.00297

    Supports the statement that earlier Bayesian work used prior information to estimate an EEG reference.

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