No, the videos didn’t touch on the subject much. There are only a few places mentioning it.
There’s a few ways to decode SDRs depending on what you are doing and wish to achieve. If you are predicting a time series, which happened to be encoded using Grid Cells. Then it can be trivially decoded using linear models. Object representations, can be decoded using a classifer. And converting SDR into motor commands is a field of active research. Most implementations just use a SP as a auto-correlation learner (but I doubt it is the best approach) like it is used in a HTM based Q-ish learner.