Dear SPMlers,
we have conducted a Working Memory study in H2O-PET with the following
design:
8 subject
4 Conditions:
A: WM 1 (high load)
B: WM 1 (low load)
C: WM 2 (high load)
D: WM 2 (low load)
3 Scans/per condition/subject
Thus we have a total of 96 scans.
To look for the main effect of Working memory and for the domain
specific effect we have chosen the Multi-subject: cond x Subj
interaction & covariates design. We find nice WM main effects and also
interesting domain specific effects.
Experimental question: We are interested if there is a correlation
between performance (as measured by RT) and WM-specific activation.
What kind of design do we have to choose?
As we work mainly with fMRI-studies we first thought of a second level
analysis. That is: Formulate subjects specific contrast, e.g. WM 1 high
load minus WM 1 low load on the first level, then feed the eight
resulting con-images into basic models (simple regression) and chosse
the median of the RT for the three WM 1 high load scans as covariates
into this modell. Then our analysis should yield regions in which there
is a correlation of one WM domain with performance.
Question 1: Is this analysis correct?
Question 2: There are several options at the first level in which it is
possible to specify scan specific covariates. Is it intelligible to
choose one of these models and feed in scan specific RT in order to
answer our experimental question? If so, what is the appropriate model?
We have tried several but if we enter scans and covariates we use up all
our degrees of freedom, e.g. if we use Mulit-subj: covariates only. So
something must be wrong.
Help appreciated.
H. Walter
--
Dr. Dr. Henrik Walter
Abteilung Psychiatrie III
Universitätsklinikum Ulm
Leimgrubenweg 12
89075 Ulm
fon: 0731/502 1489
fax: 0731/502 1549
e-mail: [log in to unmask]
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