I ran a brms model in R with a complex three-way interaction that I am trying to decompose. See below for code. I have a multinomial dependent variable with three levels (happy/angry/fear) and multiple categorical factors: group (three levels; social anxiety, other anxiety, non-anxious) / emotion (three levels; happy, angry, fear) / percentage (four levels: 10%, 30%, 50%, 70%). I am trying to figure out how I can answer the following question: Do groups differ in their responses to emotional faces (e.g., is the socially anxious group more likely than the other groups to pick angry as their response to happy or fearful faces at any of the percentage levels? The three-way interaction was significant. My question is, how should I use emmeans to get the output I would like to answer this question? Thanks so much in advance for your response.

model code: cormod_multi <- brm(Emochoice ~ f_group + f_emotion_r + f_percentage + f_groupf_emotion_rf_percentage + (1 + f_emotion_r*f_percentage | f_ppn), data = data_mult, family = 'categorical', warmup = 1000, iter = 10000, chains = 4, cores = 10, control = list(adapt_delta = 0.95, max_treedepth = 15))