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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")
::install_github("mandymejia/fMRIscrub") devtools
<- scrub(Dat1)
s_Dat1 plot(s_Dat1)
<- Dat1[!s_Dat1$outlier_flag,] Dat1_cleaned
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.