If I am interested in understanding the effect of an interaction between treatment and covariates on the variance of my response, as well as how they may affect the mean of my response, can I write a glmm like this?

brm(bf(response ~ treatment * distance + treatment * orientation + (1|Individual), sigma ~ treatment * distance + treatment * orientation), family = Gaussian)

Can somebody please explain if sigma can be reliably used in this way to understand the effect of my covariates on the response? How does this sigma response work within the model?

Can the sigma output be trusted if I have uneven treatment groups (i.e. treatment 1 has more observations than treatment 0), or will the smaller group always display greater variance?

If anybody knows of any resources for understanding how to use this sigma term, it would be much appreciated.