Dear Nissen,
> The arrangement of the experimental condition in scan series was:
> AAAABBBBC1C1C1C1AAAABBBBC2C2C2C2AAAABBBBC3C3C3C3AAAABBBBC4C4C4C4
> AAAABBBBC1C1C1C1AAAABBBBC2C2C2C2AAAABBBBC3C3C3C3AAAABBBBC4C4C4C4
> ..........
> 144 scans in total
>
> Is it possible to apply parametric analysis condition C mixed with
> blocked condition A and B ? If possible, would you please show me the
> way to specify the parameter setting of that analysis ? Otherwise, what
> is the optimal model for the data analysis in that data set?
Yes it is. Using SPM99b you would specify the design matrix as having three
conditions (A,B & C). After giving details of these conditions you will find
a 'parametric modulation' option which allows you to specify the values of
the experimental parameter just for condition C. In your case this will be
the eight values representing the 'loading from previous learning context'
for condition C. You will need to decide what type of relationship between
this parameter and brain activity you are seeking i.e.
linear/exponential/other nonlinear, and SPM99b will then generate the
appropriate design matrix. I would give this a try and if you have any
specific problems with the design matrix specification then repost.
best wishes,
Geraint
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Dr. Geraint Rees
Wellcome Advanced Fellow, Lecturer,
Mailstop 139-74, Institute of Neurology,
California Institute of Technology, University College London,
Pasadena, 12 Queen Square,
CA 91125 London WC1N 3BG
voice (626) 395-2880
fax (626) 796-8876
web http://www.klab.caltech.edu/~geraint
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