rm_nuisIC: Remove nuisance ICs from data

In templateICAr: Estimate Brain Networks and Connectivity with ICA and Empirical Priors

Remove nuisance ICs from data

Description

Subtract estimated nuisance ICs from data matrix. If the number of nuisance ICs is not provided, will estimate using PESEL (the nuisance ICs are a rotation of the nuisance PCs).

Usage

rm_nuisIC(
  BOLD,
  DR = NULL,
  template_mean = NULL,
  Q2 = NULL,
  Q2_max = NULL,
  checkRowCenter = TRUE,
  verbose = FALSE,
  return_Q2 = FALSE
)

Arguments

BOLD	the row-centered V by T data
DR, template_mean	We need an initial estimate of the group ICs, so that we can avoid removing them during removal of the estimated noise ICs. Provide either DR if dual regression has already been calculated, or template_mean (in this context, equivalent to a GICA result) if it hasn't. Exactly one must be provided.
Q2	The number of nuisance ICs. If NULL (default) will estimate using PESEL.
Q2_max	If Q2 is NULL, PESEL's estimate will be less than or equal to Q2_max. If Q2_max is NULL (default), do not limit PESEL's estimate.
checkRowCenter	Check row means, and raise an error if they are nonzero? Default: TRUE.
verbose	If TRUE, display progress updates.
return_Q2	Return (estimated) Q2 too? Default: FALSE.

Value

The V by T data with the estimated nuisance ICs subtracted from it. If return_Q2, a list of length two: the second entry will be Q2.

templateICAr documentation built on Feb. 16, 2023, 8:14 p.m.