Sorry for not answering earlier… I don’t think your question can be straightforwardly answered with hypothesis. I would just use get the posterior samples for the relevant coefficients and see how often they are bigger, i.e. (code is just a sketch):
par_names <- c("eeg1_standard_age", "eeg1_corrected_age") #Guessing the names here, you should be able to find them from the summary of the fit
s <- posterior_samples(fit, pars = par_names)
p_standard_smaller <- mean(s[[par_names[1]]] < s[[par_names[2]]]])
Does that make sense?