Edward Justin Modestino wrote:
> hello experts,
> I have searched the archive for an answer on how to determine the high
> pass filter cutoff. There have been several answers, including an
> obscure formula, none of which I fully understood. Is there a simple
> formula for determining the high pass filter cutoff? We are conducting
> both event-related and epoch studies.
> Thanks,
> Ed Modestino
Hi Edward
I believe that the cut frequency should be determined from the characteristics of
the noise rather than the characteristics of the signal. Since a large part of
the low frequency noise is system and sequence dependent, the noise
characteristics could be determined scanning a phantom. When doing this it is
very important to use a phantom with internal structures and brain like T1 and
T2* parameters. If you make such an experiment and make power density plots of
time series from pixels near an edge (use for instance pyulear in matlab signal
processing toolbox) you will probably find something like this:
log(Power)
|
| \
| \ signal
| \ _/
| \ | | noise
| \______ |_|_______/____
| | |
| | |
| | |
-----------------------> log(Frequency)
| | |
f-cut f-paradigm f-nyquist
the slope of the low frequency noise will probably be between 1/f^2 to 1/f and
f-cut around 1/100s=0.01Hz.
In this case the simple formula would read T=100s. The signal of the paradigm
(event related or box-car) is most easily detected when it is located in the
white noise region. But this has to be assured when you set up the experimental
design.
Torben
M.Sc. Phys. Eng.
Danish Research Center of Magnetic Resonance
Hvidovre Hospital
Kettegaard Alle 30
2650 Hvidovre
Denmark
Phone: +45 3632 2978
Fax: +45 3647 0302
email: [log in to unmask]
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