Trends are not always a good thing. Sometimes trends can obscure the things that are really important. A common problem in signal processing is that measured data can be affected by signal drifts – for example, due to temperature changes in your sensor or the thing that you try to measure. To get rid of these drifts the signal can be detrended. This filtering is a standard data processing step for many applications.
However, in real-time fMRI we need to perform this detrending online, that is, while we acquire the data. This is not so trivial, so Rotem Kopel, Frank Scharnowski, and I wrote a paper about it.
Kopel R & Sladky R, Laub P, Koush Y, Robineau F, Hutton C, Weiskopf N, Vuilleumier P, Van De Ville D, Scharnowski F. No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI. NeuroImage 2019