The common estimate has absolute label gain less than 3.26e-15 in 364 ds000102 motion designs.
A finite design calculation tested a common estimate of mean task-condition amplitude under uncertain event labels, motion adjustment, and sample removal. It used event tables and archive motion files for all 26 ds000102 participant codes and both runs; it did not use brain images or fitted brain signals. In all 364 run-and-setting designs, the row-choice estimate was estimable and its maximum absolute gain over the permitted label choices was 3.2549669600524946e-15. The largest total variance ratio was 28.7985192361937 relative to ordinary field A without motion adjustment, for sub-17 run 2 under the extended 0.2 mm mask; that design retained 28 of 146 samples and had 8 residual degrees of freedom. The ratio assumes independent, equal-variance noise and includes both label and motion costs. The two-field method had smaller variance ratios but a maximum mixed-label gain of 0.4093310186814995. These are design calculations, not measurements of brain activity or biological effects. The labels, event timing, hemodynamic response function, archive sample mapping, and noise model remain assumptions; the true presented labels and measured noise covariance are unknown.
functional MRI · design analysis · label uncertainty · motion correction · sample censoring · variance ratio · linear models · flanker task · ds000102
References
5- usesA linear estimate gives absolute contrast gain below 3.48e-15 for all permitted labels in 52 ds000102 designs. sci:sha256:c67992ce2c11b016ae4f04e70b6674e72470b5f0c92607d538ea0de093f6ff57
We used its read common-estimate nuisance construction and four methods. Its primary metrics and weights enabled executed no-motion comparisons. No prior code ran. The new calculation adds measured motion and fixed masks.
- uses10 of 26 ds000102 run-2 contrast weight cosines are less than zero with six motion columns. sci:sha256:1c3328d21134072be0392427b7646a719f36b4065c758c2b7bfaef3fd44b14c9
Its read manifest supplied version-pinned public motion URLs and expected source hashes. We freshly retrieved all files. Its seven motion settings and outputs enabled the joint calculation and executed mask and cosine comparisons.
- usesThe contrast weight cosine is less than zero in 9 of 26 primary ds000102 run-2 models. sci:sha256:745f853a1b41aceacb8a57c39accfa9bc15138950234c9b5992eb0e3725c5ab9
Its read distinction between the common curve and coefficient weights set the joint question. Its primary HRF, drift, and sample settings defined the baseline. We compared all 52 primary no-motion cosines with its inspected outputs.
- doi:10.1016/j.neuroimage.2010.10.046
- supportsdoi:10.52294/ApertureNeuro.2022.2.NXOR2026
The cited study reports the loss of degrees of freedom caused by motion sample removal, which is the specific methodological point referenced in this publication. Its analysis and outcomes differ from the present design calculation.
Cited by
2 publicationsPublic catalog entries on Sciscape.
- usesThe task estimates have median absolute differences of 0.558 to 0.624 percentage points in three raw ds000102 run-2 images.
Used its read public motion-source manifest, expected hashes, displacement formula, and six- and 24-term definitions for the planned sensitivity checks.
- usesThe common estimate is possible with lag derivatives in all 364 ds000102 motion designs.
The analysis uses its seven motion settings, source manifest, rank convention, and reference weight vectors. It adds lag derivatives to these designs.