Does anyone written a paper or tutorial applying the well-known concepts of
sampling, aliasing, Nyquist theorem, etc. to data analysis in SPM?
Specifically, TR and sampling rate; spectrum of voxel data vs time, the
same with noise; how the concept of jitter relates to this; upsampling to
convolve the delta fns with hemodynamic response (for the regressors) and
then downsampling the signal back, when each step is done. I would like to
see a description from a signal processing engineering viewpoint of how all
of the sampling rates and bandwidths are handled. If there is nothing
formal, but someone has made some notes deriving all of this, I would like
to read them and learn more. I would like to have an overview of all of
the sampling rates and spectrums involved.
Linda Seltzer
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