H,, 

I have got a task with 5 conditions (p1-5) that I want to compare in a weighted fashion.
General spm first-level contrasts = [0 -2.5 -1.5 -0.5 1 3.5 0]; [p5>p4>p3>p2>p1]
How does this translate to the PPI contrast?

P.Tasks = ['0' {'baseline' 'p1' 'p2' 'p3' 'p4' 'p5' ínc'}];

%When I specified the manual contrast I got an error, this one did not run
% P.Contrasts(7).left = {[0 0 0 0 0 0 0 0 -2.5 -1.5 -0.5 1 3.5]}; % left side or positive side of contrast
% P.Contrasts(7).right = {'none'}; % right side or negative side of contrast
% P.Contrasts(7).STAT = 'T'; % T contrast
% P.Contrasts(7).Weighted = 0; % Weighting contrasts by trials. Deafult is 0 for do not weight
% P.Contrasts(7).MinEvents = 1; % min number of event need to compute this contrast
% P.Contrasts(7).name = 'Load'; % Name of this contrast

% I guess this one below just does p5+p4 > p1+p2+p3 and is not what I'm after
P.Contrasts(7).left = {'p5' 'p4'}; % left side or positive side of contrast
P.Contrasts(7).right = {'p1' 'p2 'p3'}; % right side or negative side of contrast
P.Contrasts(7).STAT = 'T'; % T contrast
P.Contrasts(7).Weighted = 0; % Wieghting contrasts by trials. Deafult is 0 for do not weight
P.Contrasts(7).MinEvents = 1; % min number of event need to compute this contrast
P.Contrasts(7).name = 'Load'; % Name of this contrast

I now solved this issue by changing my 1st level by combining p1-5 in one parametric modulator regressor, but was wondering if there is a solution using the former first-level model .

Best, Stella

Dear experts,

I was wondering if anyone found a way to do this within gPPI.

Originally posted by s dewit: