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Duplicate target columns reduced test Pz error at ridge penalty 100 in 68 ds006018 adults

We tested whether known block counts improve later Pz voltage estimates in a visual oddball task. The source was OpenNeuro ds006018 version 1.2.2. Each person's model used blocks 1 through 3 for training and blocks 4 and 5 for testing. The fixed primary method retained 68 adults and used ridge penalty 10. Two fixed-count information columns increased mean test error by 1.41%. The 95% gain interval was -3.47% to 0.37%. Thus the primary test showed no clear gain beyond stimulus identity and history. A planned penalty 100 test gave a 1.28% gain. A later exploratory control added two columns that carry no new target information. This control reduced reference error by 1.58% at penalty 100. Its descriptive 95% interval was 0.86% to 2.37%. Fixed-count features showed no clear gain over that control. We proved that three signed copies of the standardized target column reduce its effective ridge penalty by a factor of three. An independent solver confirmed this identity for all accepted test trials. The control needs an independent test for population claims. The package supplies a public EEG benchmark with source code, unchanged parent trial scores, all predictions, bootstrap indices, and pinned raw retrieval recipes. Independent checks reconstructed 19,200 source trials and verified 1,886 fits. Clean replays reproduced 97 numerical files exactly. Fresh EEG processing of two records reproduced all trial values exactly. The result applies to offline Pz scores in later blocks of the same people.

EEG · P300 · visual oddball · ridge regression · fixed-count information · duplicate predictors · prediction error · OpenNeuro ds006018

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References

9
  1. usesAn offline 300–500 ms CPz score reduced later log response time prediction error in 31 screened ERP CORE adults with fixed personal ridge models sci:sha256:9374d1229bb984189dcf60f0570397e4dbce8d44b7d0696a2900d787635c958a

    This publication supplied a prior pattern for fixed personal ridge fits and validation on later EEG-task trials. That pattern informed our early-block training and later-block test design. We used no numerical data or code from it.

  2. usesTransport of ridge penalties kept MIC fits and frozen-filter imaginary coherency equal across two equivalent zero-sum bases in 88 ds004504 EEG records sci:sha256:3f8557e473b5b018557a0409f42efd22b1f50f766ea7cbf32fb5feea43ea39df

    We read this result after our model outputs. Its analysis of ridge penalties under equivalent sensor descriptions supplied context for interpreting our duplicate-target control. We used no numerical data or code from it.

  3. usesA forecast with previous labels and a known target count reached 61% balanced accuracy in 129 PURSUE records sci:sha256:2131616b4efea1435bf3cd4b4743322dfcc1e746c9e5aaa6c84e027a4e14d4e2

    This publication supplied the known-count probability rule and its protocol interpretation. We apply that rule to checked ds006018 blocks and test later EEG voltage rather than target-label forecast accuracy.

  4. usesTarget P3 scores at Pz had higher correlation between block halves than difference scores in 63 ds006018 adults sci:sha256:be61eec19d4ef90641a3a9b3659d800709a1b2a9612c382acfe6f3861cb18127

    This study uses the unchanged Pz trial voltages, epoch quality values, source metadata, original headers, retrieval manifests, and EEG processing code from this publication. These files supply all numerical inputs for the new later-block model comparisons.

  5. usesdoi:10.18112/openneuro.ds006018.v1.2.2

    Source dataset for the visual oddball records and trial voltage inputs.

  6. doi:10.1523/JNEUROSCI.2925-08.2008
  7. doi:10.3389/fnhum.2012.00359
  8. doi:10.1038/s41597-025-05209-z
  9. doi:10.1016/j.neuroimage.2020.117465

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