Linear response filling reduced a known contrast on average in 431 AOMIC working memory designs with unchanged full designs and a 0.2 mm motion limit
We tested linear filling of removed response samples in 431 public AOMIC working memory designs. The full fit designs stayed unchanged. The primary rule removed the first scan and scans with framewise displacement above 0.2 mm. All response signals were constructed; no BOLD image was used. The mean loss of a known unit task contrast was 5.10% in PIOP1 and 2.11% in PIOP2. Of the 431 runs, 374 had a loss, 23 had a gain, and 34 were unchanged within the stated tolerance. We calculated sharp false-contrast bounds for modeled nuisance signals with a true task contrast of zero. The mean bound was 0.35656 and 0.25005 when nuisance RMS on retained scans was at most one. Saved signals reached these bounds. Filling only the task columns preserved the known task contrast but left a nonzero nuisance bound. An added check with an RMS limit over the full run had mean bounds of 0.26063 and 0.20721. Independent checks passed for 3,447 valid run-setting fits and 431 primary bound signals. Fresh-source and offline repeats matched all 11 result files byte for byte. The package contains source inputs, hashes, code, proofs, results, figures, and repeat instructions. The findings apply to the stated designs, masks, model, and fill rule. They do not estimate a neural effect in measured fMRI.
functional MRI · motion censoring · linear interpolation · task contrast · nuisance signal · signal processing · AOMIC
References
6- usesTreating linearly filled response and design rows as independent made standard errors too small in 431 AOMIC designs with fixed masks and known white noise sci:sha256:063af544b223d12f520343dbfa70e6dee0b5cd0ed03f022553bb5c24754bffb6
This publication supplied the preserved public inputs, fixed design builder, and retrieval scripts. It also identified response-only filling with an unchanged full design as an open question about mean error. We tested that operation and saved exact task transfer, nuisance bounds, and bound-reaching signals.
- usesAn innovation filter matched dense GLS in 431 AOMIC designs with known stationary AR(2) noise, coefficients (0.6, 0.2), and marginal variance one sci:sha256:45fcfa6b38baf8ac44c59bfce51e800e7cfea98759f7a609ebb1a2aed6659a64
We used the unchanged AOMIC source loader and event and motion retrieval scripts from this publication through the parent package. These scripts supplied the task design, motion columns, pinned source records, and source-file checks.
- usesdoi:10.18112/openneuro.ds002785.v2.0.0
The study used event tables, motion records, and scan metadata from AOMIC PIOP1 version 2.0.0.
- usesdoi:10.18112/openneuro.ds002790.v2.0.0
The study used event tables, motion records, and scan metadata from AOMIC PIOP2 version 2.0.0.
- doi:10.1038/s41597-021-00870-6
- doi:10.3389/fnins.2022.1017211
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