Dear SPM'ers,
I ran a PET study where subects had to perform a same task under two conditions (A & B), and I want to know regions where the performance measure (covariate P) is differentially affected by condition. In SPM96, the usual way to test this question was to build a covariate of interest which was the interaction between performance (P) and conditions (A and B specified as a vector of 1 -1 ). The two members of the interaction were also entered as counfound to disclose only those regions were the performance was significantly more correlated with rCBF in condition A than in condition B.
This strategy will certainly work also in SPM99b, but I was wondering if the same result is obtained using factor by covariate interactions in the PET statistic "Multi-subj: conditions & covariates". In this case, one have first to specify which scans below to each condition A and B. Afterwards the option is proposed for the interaction between the covariate vector (the performance measure P) and conditions. In the resulting design matrix, there ar four columns "of interest" : two for conditions A and B, one for the interaction A X P, and one for the interaction B X P. Hence I have two related questions :
1. If i compute a contrast (1 -1) between AXP and BXP, am I right to expect to disclose the same regions as in the SPM96 procedure describe above ?
2. Are the coufounds controlled in the same way ? Or in other words, did this procedure control for the influence of the two members of the interaction, leaving only the product of their interaction ?
Many thanks for your help
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PEIGNEUX Philippe, Lic. Psych., Chercheur
E-mail: [log in to unmask]
Cyclotron Research Centre
Neurology Unit & Neuropsychology Department
Liege University BELGIUM
http://www.ulg.ac.be/neuropsy/
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