GLM model for fMRI data

Creates a model specification for fMRI data using a normal distribution. This model assumes that the observed BOLD signal follows a normal distribution with a mean determined by the design matrix and betas, and a standard deviation parameter for noise.

Usage

MRI()

Value

A list containing model specification

Details

The model uses a normal distribution to model fMRI BOLD signals. Beta parameters represent the effect sizes for different conditions, and the sd parameter represents the standard deviation of the noise.

The log-likelihood function centers the predicted values by subtracting the mean, which helps with model identifiability.

Examples

# Create a normal MRI model specification
model_spec <- MRI()

# Access model parameters
model_spec$p_types
#> beta   sd 
#>    0    0