If your full model has no other coefficients, then drop the coef argument to your set_prior call. Otherwise, unfortunately last I knew this isn’t straightforwardly possible with brms. You could try updating to the latest development version just in case it’s changed recently, but here’s where things stand to my knowledge
However, it’s possible that you might be able to achieve this in a sneaky way using the nonlinear syntax of brms. I haven’t tested or verified this at all, but something like:
bf(
y ~ a + b,
a ~ other covariates,
b ~ 0 + mo(x),
nl = TRUE
)
with
prior1 <- prior(some prior on the other terms, nlpar = "a") +
prior("normal(0,5)", class="b", lb=0, nlpar = "b")