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.
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.