Both detrending and removing the mean are essentially removing low-frequency baseline variations or a constant offset, respectively (or both). If these are not part of the process you are modeling (so are instead properties of the data acquisition equipment for instance) removing them would be useful.
For both of these, I generally use a highpass or bandpass digital filter (bandpass also to remove high-frequency noise) on the data first, since the filter design permits filtering the the mean as well as specifying the low-frequency cutoff. There may be advantages to using detrend for this, however for me, using a filter is easier. Filters are also relatively straightforward to design in MATLAB.
