activations: Activations of (s)tICA

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

Activations of (s)tICA

Description

Identify areas of activation in each independent component map

Usage

activations(
  tICA,
  u = 0,
  alpha = 0.01,
  type = ">",
  method_p = "BH",
  verbose = FALSE,
  which.ICs = NULL,
  deviation = FALSE
)

Arguments

tICA	Fitted (spatial) template ICA object from templateICA.
u	Activation threshold. Default: 0.
alpha	Significance level for joint PPM. Default: 0.01.
type	Type of region. Default: ">" (positive excursion region).
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).
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 and the joint and marginal PPMs for each IC. 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 Feb. 16, 2023, 8:14 p.m.