AIC penalizes complex models less, meaning that it may put more emphasis on model performance, on the training dataset and in turn, select more complex models.
BIC penalizes the model more for its complexity, meaning that more complex models will have a worse (larger) score and will, in turn, be less likely to be selected. It favours simple models.
The use in MIMO will be dependent on the research paper application you are referring to.
