Compcors the input matrix using SVD and returns the result.

Compcors the input matrix using SVD and returns the result.

compcor(
  fmri,
  ncompcor = 4,
  variance_extreme = 0.975,
  mask = NULL,
  randomSamples = 1,
  returnv = FALSE,
  returnhighvarmat = FALSE,
  returnhighvarmatinds = FALSE,
  highvarmatinds = NA,
  scale = TRUE
)

Arguments

fmri

input fmri image or matrix
ncompcor

n compcor vectors
variance_extreme

high variance threshold e.g 0.95 for 95 percent
mask

optional mask for image
randomSamples

take this many random samples to speed things up
returnv

return the spatial vectors
returnhighvarmat

bool to return the high variance matrix
returnhighvarmatinds

bool to return the high variance matrix indices
highvarmatinds

index list
scale

scale the matrix of high variance voxels, default FALSE. note that you may get slightly different results by scaling the input matrix before passing into this function.

Value

dataframe of nuisance predictors is output

Author

Avants BB

Examples


mat <- matrix( rnorm(50000) ,ncol=500)
compcorrdf<-compcor( mat )