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Whitening before scan removal gave 0.96% to 11.94% null rejection in 431 AOMIC t tests with known AR(1) rho 0.4 and Gaussian artifact SD 10

We tested whether residual variance estimation restores a 5% t test after motion scan removal. We used 431 fixed AOMIC working memory designs. We whitened each full scan grid, removed transformed rows at marked original scan times, and fitted ordinary least squares. Clean noise was stationary Gaussian AR(1), with known rho 0.4 and marginal variance one. Independent Gaussian artifacts had standard deviation ten at scans with FD greater than 0.2 mm. Calculated null rejection ranged from 0.96% to 11.94%. Rates were outside 4% to 6% in 235 designs. Cohort means were 5.000% and 4.828%. The package provides a fixed Gaussian covariance tool for the complete residual t probability. A second integral agreed within 3.6e-14. Eight public designs passed 100,000-response simulation checks. Correct scan gap GLS and whitened spike fits agreed in all 431 designs. An offline repeat matched every result byte. A clean installation passed all checks and reproduced all values within stated tolerances. Code, proof, inputs, source hashes, results, and instructions are preserved. These are conditional model probabilities. No measured brain signal was analyzed. The study does not establish actual artifact sizes or deployed pipeline error rates.

scan removal · temporal whitening · AR(1) · t tests · Gaussian covariance · null rejection probability · fMRI · motion · residual variance

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References

6
  1. usesA scan gap transform matched dense GLS in 431 AOMIC working memory designs with fixed AR(1) covariance and rho 0.4 sci:sha256:ae6c08983c3fd03d0b20cd6d91556e44c7d7a934f3e478bfefcb92fb230f7464

    We used its 431 fixed AOMIC event, motion, and image metadata inputs. We kept its design builder and scan gap whitening code unchanged. We extended its removed-scan influence check to residual t tests under Gaussian artifacts.

  2. usesBoth cohorts had 95% intervals that included zero for mean extra log contrast variance from motion mask timing in 431 AOMIC v2.0.0 working memory designs with fixed white noise sci:sha256:044463f720d58b5a648cb98667f1d2d085da23c7a7e3a169ead69bb00da47a91

    We used its event and motion design builder and retrieval records through publication 8484a887-f8de-468a-b3be-bd7355add843. The inherited code hashes and fixed source paths are preserved.

  3. usesdoi:10.18112/openneuro.ds002785.v2.0.0

    The publication used the AOMIC PIOP1 dataset, version 2.0.0, for 207 complete working memory designs and recorded motion inputs.

  4. usesdoi:10.18112/openneuro.ds002790.v2.0.0

    The publication used the AOMIC PIOP2 dataset, version 2.0.0, for 224 complete working memory designs and recorded motion inputs.

  5. doi:10.1038/s41597-021-00870-6
  6. supportsdoi:10.1093/biomet%2F38.3-4.481

    The independent characteristic-function validation uses the Gil-Pelaez inversion formula cited in the source publication.

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