Skip to content

Calculate Leverage of Component Models

Notifications You must be signed in to change notification settings

parlakfatma/fMRIscrub

This branch is up to date with mandymejia/fMRIscrub:master.

Folders and files

NameName
Last commit message
Last commit date
Jan 26, 2023
Jun 7, 2023
Mar 27, 2021
Jun 12, 2020
Jun 7, 2023
Jun 7, 2023
Jan 26, 2023
Mar 11, 2023
Jun 7, 2023
Sep 27, 2021
May 27, 2023
Jun 6, 2023
Jan 26, 2023
Jan 25, 2023
Jan 25, 2023
Mar 9, 2022
Jun 7, 2023
Apr 19, 2022

Repository files navigation

fMRIscrub

R-CMD-check Codecov test coverage

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.

Installation

You can install the development version of fMRIscrub from GitHub with:

# install.packages("devtools")
devtools::install_github("mandymejia/fMRIscrub")

Quick start guide

s_Dat1 <- scrub(Dat1)
plot(s_Dat1)
Dat1_cleaned <- Dat1[!s_Dat1$outlier_flag,]

Data

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).

Vignette

See this link to view the tutorial vignette.

Citation

If using projection scrubbing, you can cite our pre-print at https://arxiv.org/abs/2108.00319.

About

Calculate Leverage of Component Models

Resources

Citation

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • R 95.7%
  • TeX 4.3%