MRI: GLM model for fMRI data

In EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

GLM model for fMRI data

Description

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()

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.

Value

A list containing model specification

Examples

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

# Access model parameters
model_spec$p_types

EMC2 documentation built on Dec. 2, 2025, 9:06 a.m.