Dear SPM experts,
I would like to know if, in a fixed model for a fMRI study (modelled with a
Box-Car), the convolution with hrf function is always the better choice or
it depends from the interscan interval. I'm right if I make a convolution
if the interscan interval is 15 sec. and each condition has 5 scans?
The second question is about temporal smoothing: selecting a Low-pass
filter (hrf) the effective degrees of freedom become 80.98 (instead of 81).
What is the meaning of a not integer value for this variable?
The last doubt I have (...for the moment...) is: I read somewhere in a mail
(that I've lost) that, if I make Global Normalization in a fixed model for
each subject, the second level statistic between subjects for a given
contrast doesn't need again this option (also 'Grand mean scaling'). If I
remember well what I have read, I don't understand why they are not
necessary.
Thanks a lot for your help.
Eleonora
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Eleonora FORNARI
Signal Processing Laboratory
Swiss Federal Institute of Technology
CH-1015 Lausanne
Switzerland
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