activations: Identify field activations

Description

Identify areas of activation for each field from the result of BayesGLM or fit_bayesglm.

Usage

activations(
  x,
  Bayes = TRUE,
  gamma = NULL,
  alpha = 0.05,
  correction = c("FWER", "FDR", "none"),
  fields = NULL,
  sessions = NULL,
  verbose = 1
)
id_activations(
  x,
  Bayes = TRUE,
  gamma = NULL,
  alpha = 0.05,
  correction = c("FWER", "FDR", "none"),
  fields = NULL,
  sessions = NULL,
  verbose = 1
)

Value

An "act_BGLM" or "act_fit_bglm" object, a list which indicates the activated locations along with related information.

Arguments

x: Result of BayesGLM or fit_bayesglm model call, of class "BGLM" or "fit_bglm".
Bayes: Use spatial Bayesian modeling to identify activations based on the joint posterior distribution? Default: TRUE. If FALSE, activations will be based on classical (massive univariate) GLM model, with multiple comparisons correction (see correction). Note that TRUE is only applicable if x includes Bayesian results (i.e. x <- BayesGLM(..., Bayes = TRUE) was run.)
gamma: Activation threshold, for example 1 for 1 percent signal change if scale_BOLD=="mean" during model estimation. Setting a gamma is required for the Bayesian method; NULL (default) will use a gamma of zero for the classical method.
alpha: Significance level for inference. Default: 0.05.
correction: For the classical method only: Type of multiple comparisons correction: "FWER" (Bonferroni correction, the default), "FDR" (Benjamini Hochberg), or "none".
fields: The field(s) to identify activations for. Give either the name(s) as a character vector, or the numerical indices. If NULL (default), analyze all fields.
sessions: The session(s) to identify activations for. Give either the name(s) as a character vector, or the numerical indices. If NULL (default), analyze the first session.
verbose: 1 (default) to print occasional updates during model computation; 2 for occasional updates as well as running INLA in verbose mode (if Bayes), or 0 for no printed updates.