Priors for category specific terms in ordinal logistic regression

Is it possible to create separate priors for each coefficient in an ordinal logistic regression model that uses category specific terms? For example, in the model below, I would like a separate prior for each of the the var_aB[1] and var_aB[2] terms.

Looking at the results of get_prior() and prior_summary(), I don’t see any way to distinguish between the coefficients when setting a prior.

I have tried setting priors using something like:
priors ← c(prior(student_t(5, 2, 1), class = b, coef = var_aB[1]),
prior(student_t(5, 0, 1), class = b, coef = var_aB[2])
but this doesn’t seem to work.

I am using Windows 10 and brms 2.15.0.


dat <- data.frame(var_a = factor(rep(c('A', 'B'), times = 50),
                                 levels = c('A', 'B')),
                  var_b = rep(c(1, 2, 1, 2), times = 25),
                  response = factor(sample(c('low', 'mid', 'high'), size = 100, 
                                 replace = TRUE), ordered = TRUE,
                                 levels = c('low', 'mid', 'high'))) 

# Not the priors I want. Just using these as defaults.
priors <- c(prior(student_t(5, 0, 1), class = b))

# Model with category specific terms
mod <- brm(response ~ cs(var_a) + cs(var_b) + cs(var_a:var_b),
           prior = priors,
           family = cratio(),
           data = dat,
           chains = 4, cores = 4,
           seed = 77777)

# Model results. I want to be able to have separate priors for the [1] and [2] parts of each term.

Please let me know if setting separate priors for each category specific term is possible, and, if so, how to do it.

Thank you.

I didn’t find the answer in my original search, but this question has been previously answered here.