fMRIscrub
is a collection of routines for data-driven scrubbing
(projection scrubbing and DVARS), motion scrubbing, and other fMRI
denoising strategies such as anatomical CompCor, detrending, and
nuisance regression. Projection scrubbing is also applicable to other
outlier detection tasks involving high-dimensional data.
You can install the development version of fMRIscrub from GitHub with:
# install.packages("devtools")
devtools::install_github("mandymejia/fMRIscrub")
s_Dat1 <- scrub(Dat1)
plot(s_Dat1)
Dat1_cleaned <- Dat1[!s_Dat1$outlier_flag,]
Two scans from the ABIDE
I are
included in fMRIscrub
: Dat1
has many artifacts whereas Dat2
has
few visible artifacts. Both are vectorized sagittal slices stored as
numeric matrices. They are loaded into the environment upon loading the
package.
We acknowledge the corresponding funding for the ABIDE I data:
Primary support for the work by Adriana Di Martino was provided by the (NIMH K23MH087770) and the Leon Levy Foundation. Primary support for the work by Michael P. Milham and the INDI team was provided by gifts from Joseph P. Healy and the Stavros Niarchos Foundation to the Child Mind Institute, as well as by an NIMH award to MPM ( NIMH R03MH096321).
See this link to view the tutorial vignette.
If using projection scrubbing, you can cite our pre-print at https://arxiv.org/abs/2108.00319.
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