activations.posterior: Identify activations using joint posterior probabilities

In mandymejia/BayesGLMfMRI: Spatial Bayesian Methods for Task Functional MRI Studies

Identify activations using joint posterior probabilities

Description

Identifies areas of activation given an activation threshold and significance level using joint posterior probabilities

Usage

activations.posterior(x, fields, session, alpha = 0.05, gamma)

Arguments

x	Result of BayesGLM, of class "BGLM".
fields, session, alpha, gamma	See activations.

Details

For a given latent field, identifies locations that exceed a certain activation threshold (e.g. 1 percent signal change) at a given significance level, based on the joint posterior distribution of the latent field.

Value

A list with two elements: active, which gives a matrix of zeros and ones of the same dimension as x$field_estimates${session}, and excur_result, an object of class "excurobj" (see INLA's excursions.inla for more information).

mandymejia/BayesGLMfMRI documentation built on April 12, 2025, 3:41 p.m.