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Protected motion removal kept mean synthetic contrasts of 0.261 and 0.272 in 431 AOMIC working memory designs under a unit task residual RMS bound

We tested motion removal that keeps a task contrast unchanged. The motion terms were made orthogonal to the task and baseline terms. The inputs were 431 public AOMIC version 2.0.0 working memory designs: 207 PIOP1 and 224 PIOP2 runs. The target was change minus nochange. The main model used six motion terms. Each synthetic residual artifact had RMS equal to the residual unit-contrast task signal. The sharp maximum remaining contrast averaged 0.261 and 0.272 in the two cohorts. The artifact that reached each bound remained as the exact residual task shape. A joint fit gave zero contrast for these artifacts and one for a unit task signal. The bound squared also equaled one minus the base-to-joint variance ratio under independent errors. All seven fixed scenarios and 3,017 design tests are included. A reusable NumPy tool, proof, source bytes, fixed retrieval recipes, attaining signals, and separate checks are preserved. Offline and fresh source repeats matched all 17 output files exactly. These results test designs and specified artifact amplitudes. They do not measure brain activity or actual motion bias.

fMRI · motion artifacts · contrast estimation · regression · design audit · reproducibility

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References

7
  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

    This publication is the earlier source of the loader, task builder, and pinned motion retrieval plan. We inherited these files through publication f0be2d36-76ce-41c3-a239-12da66e96a06. We did not use its autoregressive results.

  2. usesResponse-only removal of six motion terms reduced known unit contrasts in 431 fixed AOMIC v2.0.0 working memory designs after shared drift removal sci:sha256:061d9a1371b95e2dddc49d3124d269c10d26416b55b4f8728ff06b3f8fa82087

    We used the archived AOMIC event files, selected motion tables, image metadata, source manifests, and four complete confound examples. We kept its loader, task builder, and source retrieval code unchanged. These inputs fixed the 431 designs for the new bounded-artifact audit.

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

    Recorded working memory events, motion columns, and image metadata from AOMIC PIOP1 version 2.0.0.

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

    Recorded working memory events, motion columns, and image metadata from AOMIC PIOP2 version 2.0.0.

  5. doi:10.1038/s41597-021-00870-6
  6. doi:10.1371/journal.pone.0126255
  7. doi:10.1002/hbm.24528

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