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.