I want to take the "raw signal" and then apply detrending (e.g. highpass
filtering at 128Hz) and temporal autocorrelation correction (e.g. using
AR(1) model) just as how ordinary SPM procedure does. I searched for a
script or a thread concerning this issue, but unfortunately I wasn't able to
find a good advice on this.
So I came up with one idea which is to use the conventional SPM model
estimation procedure *without* any regressor specified. This way, the model
matrix will only include the grand mean (column of ones) for each run. The
residuals from this estimation should, in theory, give me the "highpass
filtered" and "temporal autocorrelation corrected" which is further mean
centered for each run.
I'm curious if this is a valid way to get the raw signal detrended and
corrected for temporal autocorrelation. I would also appreciate if anyone
has a code that does such a job. Or, any comments on this issue would be