Hello. Is it possible to specify exact correlations to be estimated in the random effects variance-covariance matrix?

Let’s say that y is binomial response variable, x continuous predictor, and Cond is a binomial predictor(valued A or B).

This code

```
brms (y~x*Cond + (x*Cond | subject), data = da, family = "bernoulli", verbose = T, chains = 4, iter = 2000, warmup = 200, cores = 4, prior =c(set_prior ("normal (0, 8)"))
```

estimates all correlations between the effects that is

Intercept - X

Intercept - CondB

Intercept - X:CondB

X - CondB

X - X:CondB

CondB - X:CondB

I would like to estimate only

Intercept-CondB

X - X:CondB

to make the model simpler.

IS that possible?