activations: Activations of (spatial) template ICA

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

Activations of (spatial) template ICA

Description

Identify areas of activation in each independent component map from the result of (spatial) template ICA.

Usage

activations(
  tICA,
  u = NULL,
  z = NULL,
  alpha = 0.01,
  type = c(">", "abs >", "<", "!="),
  method_p = "BH",
  verbose = FALSE,
  which.ICs = NULL,
  deviation = FALSE
)

Arguments

tICA	Fitted (spatial) template ICA object from templateICA.
u, z	Set a threshold value for activation? A threshold value can be specified directly with u, or a z-score-like threshold in terms of standard deviations (the SD of values in the mean template) can be specified with z. Only one type of threshold can be used. Default: NULL (do not use a threshold). Either argument can also be a vector to test multiple thresholds at once, as long as type is not "!=" (to ensure the activation regions are successive subsets).
alpha	Significance level for hypothesis testing. Default: 0.01.
type	Type of region: ">" (default), "abs >", "<", or "!=". "abs >" tests for magnitude by taking the absolute value and then testing if they are greater than... .
method_p	If the input is a "tICA.[format]" model object, the type of multiple comparisons correction to use for p-values, or NULL for no correction. See help(p.adjust). Default: "BH" (Benjamini & Hochberg, i.e. the false discovery rate). Note that multiple comparisons will account for data locations, but not ICs.
verbose	If TRUE, display progress of algorithm. Default: FALSE.
which.ICs	Indices of ICs for which to identify activations. If NULL (default), use all ICs.
deviation	If TRUE identify significant deviations from the template mean, rather than significant areas of engagement. Default: FALSE.

Value

A list containing activation maps for each IC, the joint and marginal PPMs for each IC, and the parameters used for computing activation. If the input represented CIFTI- or NIFTI-format data, then the activations maps will be formatted accordingly.

Use summary to obtain information about the activations results. For CIFTI-format activations, use plot to visualize the activation maps.

Examples

## Not run: 
 activations(tICA_result, alpha=.05, deviation=TRUE)

## End(Not run)

templateICAr documentation built on April 3, 2025, 7:41 p.m.